---
description: >-
  Deep learning papers notes sharing, especially for image forgery detection and
  localization
---

# Overview

> [ccf-rankings](https://www.ccf.org.cn/en/About_CCF/Media_Center/) now marked with different colors(![arXiv](https://img.shields.io/badge/CCF_A-dc3545) ![Static Badge](https://img.shields.io/badge/CCF_B-ffc107) ![Static Badge](https://img.shields.io/badge/CCF_C-28a745) ![Static Badge](https://img.shields.io/badge/CCF_None-6c757d))
>
> Newly added papers will be organized at the top of every category now.

### Related

* [Datasets Resources](related/datasets)
* [Nice Expression](related/nice-expressions)
* [Research Methods](related/howtodoresearch) (_public information summery_)
* [Paper Resource Links](related/papersource)

### Basics

* [图像处理基础知识](basic-knowledge/image-processing)

### Backbone

**骨干网络**，多为图像分类的网络。

* [x] [Attention Is All You Need](backbone/transformer) (_NeurIPS '17_) **\[**[**Paper**](https://proceedings.neurips.cc/paper/7181-attention-is-all)**]** **\[**[**Code\_official**](https://github.com/tensorflow/tensor2tensor/blob/master/tensor2tensor/models/transformer.py)**]** **\[**[**Code\_community**](https://github.com/jadore801120/attention-is-all-you-need-pytorch)**]**
* [x] [EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks](backbone/efficientnet) (_ICML '19_) **\[**[**Paper**](https://arxiv.org/abs/1905.11946)**]** **\[**[**Code**](https://github.com/tensorflow/tpu/tree/master/models/official/efficientnet)**]**
* [x] [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](backbone/vit) (_ICLR '21_) **\[**[**Paper**](https://arxiv.org/abs/2010.11929)**]** **\[**[**Code**](https://github.com/google-research/vision_transformer)**]**
* [x] [Multi-Dimensional Model Compression of Vision Transformer](backbone/multi-dimensional-compression-vit) (_ICME '22_) **\[**[**Paper**](https://arxiv.org/abs/2201.00043)**]**
* [x] Deep Residual Learning for Image Recognition (_CVPR '16_) **\[**[**Paper**](https://arxiv.org/abs/1512.03385)**]**
* [ ] Generative Adversarial Networks (_NeurIPS '14_) **\[**[**Paper**](https://papers.nips.cc/paper/2014/hash/5ca3e9b122f61f8f06494c97b1afccf3-Abstract.html)**]**
* [ ] Masked Auto-Encoders Meet Generative Adversarial Networks and Beyond (_CVPR '23_) **\[**[**Paper**](https://feizc.github.io/resume/ganmae.pdf)**]**
* [ ] A Kernel Perspective of Skip Connections in Convolutional Networks (_ICLR '23_) **\[**[**Paper**](https://arxiv.org/abs/2211.14810)**]**
* [ ] EfficientViT: Memory Efficient Vision Transformer with Cascaded Group Attention (_CVPR '23_) **\[**[**Paper**](https://arxiv.org/abs/2305.07027)**]** **\[**[**Code**](https://github.com/microsoft/Cream/tree/main/EfficientViT)**]** **\[**[**Note\_community**](https://blog.csdn.net/P_LarT/article/details/130687567)**]**
* [ ] Vision Transformers Need Registers _(ICLR '24)_ **\[**[**Paper**](https://openreview.net/forum?id=2dnO3LLiJ1)**]**
* [ ] LiFT: A Surprisingly Simple Lightweight Feature Transform for Dense ViT Descriptors _(ECCV '24)_ **\[**[**Paper**](https://www.cs.umd.edu/~sakshams/LiFT/)**]**
* [ ] DCDepth: Progressive Monocular Depth Estimation in Discrete Cosine Domain [![paper](https://img.shields.io/badge/NeurIPS_'24-dc3545)](https://arxiv.org/abs/2410.14980) [![GitHub](https://img.shields.io/github/stars/w2kun/DCDepth?style=flat)](https://github.com/w2kun/DCDepth)
* [ ] Segment Anything [![paper](https://img.shields.io/badge/ICCV_'23-dc3545)](https://openaccess.thecvf.com/content/ICCV2023/html/Kirillov_Segment_Anything_ICCV_2023_paper.html) [![GitHub](https://img.shields.io/github/stars/facebookresearch/segment-anything?style=flat)](https://github.com/facebookresearch/segment-anything)

### Image Tampering

**图像篡改检测定位**

#### Image Editing

<details>

<summary>2025</summary>

* [ ] UGD-IML: A Unified Generative Diffusion-based Framework for Constrained and Unconstrained Image Manipulation Localization [![Static Badge](https://img.shields.io/badge/arXiv_'25-6c757d)](https://arxiv.org/abs/2508.06101)
* [ ] CLUE: Leveraging Low-Rank Adaptation to Capture Latent Uncovered Evidence for Image Forgery Localization [![Static Badge](https://img.shields.io/badge/arXiv_'25-6c757d)](https://arxiv.org/abs/2508.07413) [![GitHub](https://img.shields.io/github/stars/SZAISEC/CLUE?style=flat)](https://github.com/SZAISEC/CLUE)
* [ ] ForensicsSAM: Toward Robust and Unified Image Forgery Detection and Localization Resisting to Adversarial Attack [![Static Badge](https://img.shields.io/badge/arXiv_'25-6c757d)](https://arxiv.org/abs/2508.07402) [![GitHub](https://img.shields.io/github/stars/siriusPRX/ForensicsSAM?style=flat)](https://github.com/siriusPRX/ForensicsSAM)
* [ ] MUN: Image Forgery Localization Based on M³ Encoder and UN Decoder [![Static Badge](https://img.shields.io/badge/AAAI_'25-dc3545)](https://ojs.aaai.org/index.php/AAAI/article/view/32606) [![GitHub](https://img.shields.io/github/stars/MrHuan3/MUN?style=flat)](https://github.com/MrHuan3/MUN)
* [ ] ForensicHub: A Unified Benchmark & Codebase for All-Domain Fake Image Detection and Localization [![Static Badge](https://img.shields.io/badge/arXiv_'25-6c757d)](https://arxiv.org/abs/2505.11003) [![GitHub](https://img.shields.io/github/stars/scu-zjz/ForensicHub?style=flat)](https://github.com/scu-zjz/ForensicHub)
* [ ] AFCMS-Net: Adaptive feature coupling and multi-level supervision network for effective image forgery localization [![Static Badge](https://img.shields.io/badge/KBS_'25-28a745)](https://doi.org/10.1016/j.knosys.2025.114126) [![GitHub](https://img.shields.io/github/stars/SwallowIsXYZ/0617_AFCMS-Net?style=flat)](https://github.com/SwallowIsXYZ/0617_AFCMS-Net)
* [ ] Edge-aware Affinity Enhancement for Image Manipulation Localization [![paper](https://img.shields.io/badge/MM_'25-dc3545)](readme)
* [ ] DFPD: Dual-Forgery Proactive Defense against Both Deepfakes and Traditional Image Manipulations [![paper](https://img.shields.io/badge/MM_'25-dc3545)](readme) [![GitHub](https://img.shields.io/github/stars/imagecbj/DFPD?style=flat)](https://github.com/imagecbj/DFPD)
* [ ] Beyond Fully Supervised Pixel Annotations: Scribble-Driven Weakly-Supervised Framework for Image Manipulation Localization [![Static Badge](https://img.shields.io/badge/arXiv_'25-6c757d)](https://arxiv.org/abs/2507.13018) [![GitHub](https://img.shields.io/github/stars/vpsg-research/SCAF?style=flat)](https://github.com/vpsg-research/SCAF)
* [ ] Loupe: A Generalizable and Adaptive Framework for Image Forgery Detection [![Static Badge](https://img.shields.io/badge/IJCAI_'25-dc3545)](https://arxiv.org/abs/2506.16819) [![GitHub](https://img.shields.io/github/stars/Kamichanw/Loupe?style=flat)](https://github.com/Kamichanw/Loupe)
* [ ] M2SFormer: Multi-Spectral and Multi-Scale Attention with Edge-Aware Difficulty Guidance for Image Forgery Localization [![paper](https://img.shields.io/badge/ICCV_'25-dc3545)](https://arxiv.org/abs/2506.20922)
* [ ] Active Adversarial Noise Suppression for Image Forgery Localization [![Static Badge](https://img.shields.io/badge/arXiv_'25-6c757d)](https://arxiv.org/abs/2506.12871) [![GitHub](https://img.shields.io/github/stars/SZAISEC/ANSM?style=flat)](https://github.com/SZAISEC/ANSM)
* [ ] Can We Get Rid of Handcrafted Feature Extractors? SparseViT: Nonsemantics-Centered, Parameter-Efficient Image Manipulation Localization through Spare-Coding Transformer [![Static Badge](https://img.shields.io/badge/AAAI_'25-dc3545)](https://arxiv.org/abs/2412.14598) [![GitHub](https://img.shields.io/github/stars/scu-zjz/SparseViT?style=flat)](https://github.com/scu-zjz/SparseViT)
* [ ] Let Images Speak More: An Efficient Method for Detecting Image Manipulation History [![Static Badge](https://img.shields.io/badge/TCSVT_'25-ffc107)](https://ieeexplore.ieee.org/abstract/document/11007490) [![GitHub](https://img.shields.io/github/stars/CherishL-J/Op-detection?style=flat)](https://github.com/CherishL-J/Op-detection)
* [ ] EAN: Edge-Aware Network for Image Manipulation Localization [![Static Badge](https://img.shields.io/badge/TCSVT_'25-ffc107)](https://ieeexplore.ieee.org/abstract/document/10705343)
* [ ] Unravelling Digital Forgeries: A Systematic Survey on Image Manipulation Detection and Localization [![Static Badge](https://img.shields.io/badge/ACM_Computing_Surveys_'25-6c757d)](https://doi.org/10.1145/3731243)
* [ ] Self-Optimization Training for Weakly Supervised Image Manipulation Localization [![Static Badge](https://img.shields.io/badge/ICASSP_'25-ffc107)](https://ieeexplore.ieee.org/abstract/document/10889843)
* [ ] KLMN: Knowledge distillation based lightweight multi-clue image forgery detection and localization [![Static Badge](https://img.shields.io/badge/ICASSP_'25-ffc107)](https://ieeexplore.ieee.org/abstract/document/10888764)
* [ ] Image manipulation localization via semantic-guided feature enhancement and deep multi-scale edge supervision [![Static Badge](https://img.shields.io/badge/Neurocomputing_'25-28a745)](https://doi.org/10.1016/j.neucom.2025.130255)
* [ ] Reinforced Multi-teacher Knowledge Distillation for Efficient General Image Forgery Detection and Localization [![Static Badge](https://img.shields.io/badge/AAAI_'25-dc3545)](https://arxiv.org/abs/2504.05224)
* [ ] A Lightweight and Effective Image Tampering Localization Network with Vision Mamba [![Static Badge](https://img.shields.io/badge/SPL_'25-28a745)](https://arxiv.org/abs/2502.09941) [![GitHub](https://img.shields.io/github/stars/multimediaFor/ForMa?style=flat)](https://github.com/multimediaFor/ForMa)
* [ ] Robustifying vision transformer for image forgery localization with multi-exit architectures [![Static Badge](https://img.shields.io/badge/PR_'25-ffc107)](https://www.sciencedirect.com/science/article/pii/S0031320325002250)
* [ ] A Semantically Impactful Image Manipulation Dataset: Characterizing Image Manipulations using Semantic Significance [![Static Badge](https://img.shields.io/badge/WACV_'25-ffc107)](https://openaccess.thecvf.com/content/WACV2025/html/Chen_A_Semantically_Impactful_Image_Manipulation_Dataset_Characterizing_Image_Manipulations_using_WACV_2025_paper.html) [![GitHub](https://img.shields.io/github/stars/csiimd/csiimd?style=flat)](https://github.com/csiimd/csiimd)
* [ ] FakeShield: Explainable Image Forgery Detection and Localization via Multi-modal Large Language Models [![Static Badge](https://img.shields.io/badge/ICLR_'25-6c757d)](https://arxiv.org/abs/2410.02761) [![GitHub](https://img.shields.io/github/stars/zhipeixu/FakeShield?style=flat)](https://github.com/zhipeixu/FakeShield) _❗Updated_
* [ ] SIDA: Social Media Image Deepfake Detection, Localization and Explanation with Large Multimodal Model [![Static Badge](https://img.shields.io/badge/CVPR_'25-dc3545)](http://arxiv.org/abs/2412.04292) [![GitHub](https://img.shields.io/github/stars/hzlsaber/SIDA?style=flat)](https://github.com/hzlsaber/SIDA)_❗Updated_
* [ ] OmniGuard: Hybrid Manipulation Localization via Augmented Versatile Deep Image Watermarking [![Static Badge](https://img.shields.io/badge/CVPR_'25-dc3545)](https://arxiv.org/abs/2412.01615) [![GitHub](https://img.shields.io/github/stars/xuanyuzhang21/OmniGuard?style=flat)](https://github.com/xuanyuzhang21/OmniGuard)
* [ ] Forensics-Bench: A Comprehensive Forgery Detection Benchmark Suite for Large Vision Language Models [![Static Badge](https://img.shields.io/badge/CVPR_'25-dc3545)](https://arxiv.org/abs/2503.15024) [![GitHub](https://img.shields.io/github/stars/Forensics-Bench/Forensics-Bench?style=flat)](https://github.com/Forensics-Bench/Forensics-Bench)
* [ ] Weakly-supervised cross-contrastive learning network for image manipulation detection and localization [![Static Badge](https://img.shields.io/badge/KBS_'25-28a745)](https://doi.org/10.1016/j.knosys.2025.113033)
* [ ] Dual-decoding branch contrastive augmentation for image manipulation localization [![Static Badge](https://img.shields.io/badge/KBS_'25-28a745)](https://www.sciencedirect.com/science/article/pii/S0950705124014102)
* [ ] PIM-Net: Progressive Inconsistency Mining Network for image manipulation localization [![Static Badge](https://img.shields.io/badge/PR_'25-ffc107)](https://www.sciencedirect.com/science/article/pii/S0031320324008872)
* [ ] UFG-Net: Uncertainty and frequency guided network for image forgery localization [![Static Badge](https://img.shields.io/badge/Neurocomputing_'25-28a745)](https://doi.org/10.1016/j.neucom.2025.129471)
* [ ] PRest-Net: Multi-domain Probability Estimation Network for Robust Image Forgery Detection [![Static Badge](https://img.shields.io/badge/TOMM_'25-ffc107)](https://dl.acm.org/doi/pdf/10.1145/3711930)
* [ ] Exploring multi-scale forgery clues for stereo super-resolution image forgery localization [![Static Badge](https://img.shields.io/badge/PR_'25-ffc107)](https://doi.org/10.1016/j.patcog.2024.111230)
* [ ] Mesoscopic Insights: Orchestrating Multi-scale & Hybrid Architecture for Image Manipulation Localization [![Static Badge](https://img.shields.io/badge/AAAI_'25-dc3545)](https://arxiv.org/abs/2412.13753) [![GitHub](https://img.shields.io/github/stars/scu-zjz/Mesorch?style=flat)](https://github.com/scu-zjz/Mesorch)
* [ ] SAFIRE: Segment Any Forged Image Region [![Static Badge](https://img.shields.io/badge/AAAI_'25-dc3545)](https://arxiv.org/abs/2412.08197) [![GitHub](https://img.shields.io/github/stars/mjkwon2021/SAFIRE?style=flat)](https://github.com/mjkwon2021/SAFIRE)

</details>

<details>

<summary>2024</summary>

* [ ] Employing Reinforcement Learning to Construct a Decision-making Environment for Image Forgery Localization [![paper](https://img.shields.io/badge/TIFS_'24-dc3545)](https://ieeexplore.ieee.org/abstract/document/10478835) [![GitHub](https://img.shields.io/github/stars/tansq/CoDE?style=flat)](https://github.com/tansq/CoDE)
* [ ] Learning Compressed Artifact for JPEG Manipulation Localization Using Wide-Receptive-Field Network [![Static Badge](https://img.shields.io/badge/TOMM_'24-ffc107)](https://doi.org/10.1145/3678883)
* [ ] Proactive image manipulation detection via deep semi-fragile watermark [![Static Badge](https://img.shields.io/badge/Neurocomputing_'24-28a745)](https://doi.org/10.1016/j.neucom.2024.127593)
* [ ] Multi-domain Probability Estimation Network for Forgery Detection over Online Social Network Shared Images [![conf](https://img.shields.io/badge/ICME_'24-ffc107)](https://ieeexplore.ieee.org/document/10687645)
* [ ] Dual Hypergraph Convolution Networks for Image Forgery Localization [![Static Badge](https://img.shields.io/badge/ICPR_'24-28a745)](https://doi.org/10.1016/j.neucom.2024.128607)
* [ ] DiRLoc: Disentanglement Representation Learning for Robust Image Forgery Localization [![Static Badge](https://img.shields.io/badge/TDSC_'24-dc3545)](https://doi.ieeecomputersociety.org/10.1109/TDSC.2024.3522190)
* [ ] SUMI-IFL: An Information-Theoretic Framework for Image Forgery Localization with Sufficiency and Minimality Constraints [![Static Badge](https://img.shields.io/badge/arXiv_'24-6c757d)](http://arxiv.org/abs/2412.09981)
* [ ] Image Forgery Localization with State Space Models [![Static Badge](https://img.shields.io/badge/arXiv_'24-6c757d)](https://arxiv.org/abs/2412.11214) [![GitHub](https://img.shields.io/github/stars/multimediaFor/LoMa?style=flat)](https://github.com/multimediaFor/LoMa)
* [ ] PhotoHolmes: a Python library for forgery detection in digital images [![Static Badge](https://img.shields.io/badge/arXiv_'24-6c757d)](https://arxiv.org/abs/2412.14969) [![GitHub](https://img.shields.io/github/stars/photoholmes/photoholmes?style=flat)](https://github.com/photoholmes/photoholmes)
* [ ] A Novel Universal Image Forensics Localization Model Based on Image Noise and Segment Anything Model [![Static Badge](https://img.shields.io/badge/IH\&MMSec_'24-28a745)](https://doi.org/10.1145/3658664.3659639)
* [ ] Omni-IML: Towards Unified Image Manipulation Localization [![Static Badge](https://img.shields.io/badge/arXiv_'24-6c757d)](http://arxiv.org/abs/2411.14823)
* [ ] ForgerySleuth: Empowering Multimodal Large Language Models for Image Manipulation Detection [![Static Badge](https://img.shields.io/badge/arXiv_'24-6c757d)](http://arxiv.org/abs/2411.19466) [![GitHub](https://img.shields.io/github/stars/sunzhihao18/ForgerySleuth?style=flat)](https://github.com/sunzhihao18/ForgerySleuth)
* [ ] Dual JPEG Compatibility: a Reliable and Explainable Tool for Image Forensics [![Static Badge](https://img.shields.io/badge/arXiv_'24-6c757d)](http://arxiv.org/abs/2408.17106)
* [ ] Is JPEG AI going to change image forensics? [![Static Badge](https://img.shields.io/badge/arXiv_'24-6c757d)](https://arxiv.org/abs/2412.03261)
* [ ] Image Forgery Localization via Guided Noise and Multi-Scale Feature Aggregation [![Static Badge](https://img.shields.io/badge/arXiv_'24-6c757d)](https://arxiv.org/abs/2412.01622)
* [ ] Image manipulation localization via dynamic cross-modality fusion and progressive integration [![Static Badge](https://img.shields.io/badge/Neurocomputing_'24-28a745)](https://doi.org/10.1016/j.neucom.2024.128607)
* [ ] HRGR: Enhancing Image Manipulation Detection via Hierarchical Region-aware Graph Reasoning [![Static Badge](https://img.shields.io/badge/arXiv_'24-6c757d)](https://arxiv.org/abs/2410.21861)
* [ ] Language-guided Hierarchical Fine-grained Image Forgery Detection and Localization (HiFi-Net++) [![paper](https://img.shields.io/badge/IJCV_'24-dc3545)](https://arxiv.org/abs/2410.23556) [![GitHub](https://img.shields.io/github/stars/CHELSEA234/HiFi_IFDL?style=flat)](https://github.com/CHELSEA234/HiFi_IFDL)
* [ ] Image Manipulation Detection With Implicit Neural Representation and Limited Supervision [![conf](https://img.shields.io/badge/ECCV_'24-ffc107)](https://www.ecva.net/papers/eccv_2024/papers_ECCV/papers/12164.pdf)
* [ ] AdaIFL: Adaptive Image Forgery Localization via a Dynamic and Importance-aware Transformer Network [![conf](https://img.shields.io/badge/ECCV_'24-ffc107)](https://www.ecva.net/papers/eccv_2024/papers_ECCV/papers/06023.pdf)
* [ ] Noise-assisted Prompt Learning for Image Forgery Detection and Localization [![conf](https://img.shields.io/badge/ECCV_'24-ffc107)](https://www.ecva.net/papers/eccv_2024/papers_ECCV/papers/01688.pdf)
* [ ] Learning Universal Features for Generalizable Image Forgery Localization [![Static Badge](https://img.shields.io/badge/OpenReview-6c757d)](https://openreview.net/forum?id=OKzvovmUbh) [![GitHub](https://img.shields.io/github/stars/ZhaoHengrun/GIFL?style=flat)](https://github.com/ZhaoHengrun/GIFL)
* [ ] A Large-scale Interpretable Multi-modality Benchmark for Image Forgery Localization [![Static Badge](https://img.shields.io/badge/OpenReview-6c757d)](https://openreview.net/forum?id=7AvYFqcNfn)
* [ ] ForgeryTTT: Zero-Shot Image Manipulation Localization with Test-Time Training [![Static Badge](https://img.shields.io/badge/arXiv_'24-6c757d)](https://arxiv.org/abs/2410.04032)
* [ ] ForgeryGPT: Multimodal Large Language Model For Explainable Image Forgery Detection and Localization [![Static Badge](https://img.shields.io/badge/arXiv_'24-6c757d)](https://arxiv.org/abs/2410.10238)
* [ ] FakeBench: Probing Explainable Fake Image Detection via Large Multimodal Models [![Static Badge](https://img.shields.io/badge/arXiv_'24-6c757d)](https://arxiv.org/abs/2404.13306) [![GitHub](https://img.shields.io/github/stars/Yixuan423/FakeBench?style=flat)](https://github.com/Yixuan423/FakeBench)
* [ ] EL-FDL: Improving Image Forgery Detection and Localization via Ensemble Learning [![conf](https://img.shields.io/badge/ICANN_'24-28a745)](https://link.springer.com/chapter/10.1007/978-3-031-72335-3_17)
* [ ] Unified Frequency-Assisted Transformer Framework for Detecting and Grounding Multi-Modal Manipulation [![paper](https://img.shields.io/badge/IJCV_'24-dc3545)](https://arxiv.org/abs/2309.09667)
* [ ] Detecting and Grounding Multi-Modal Media Manipulation and Beyond [![paper](https://img.shields.io/badge/TPAMI_'24-dc3545)](https://ieeexplore.ieee.org/abstract/document/10440475/) [![GitHub](https://img.shields.io/github/stars/rshaojimmy/MultiModal-DeepFake?style=flat)](https://github.com/rshaojimmy/MultiModal-DeepFake)
* [ ] FastForensics: Efficient Two-Stream Design for Real-Time Image Manipulation Detection [![conf](https://img.shields.io/badge/BMVC_'24-28a745)](https://doi.org/10.1016/j.knosys.2024.111988)
* [ ] Auto-focus tracing: Image manipulation detection with artifact graph contrastive [![Static Badge](https://img.shields.io/badge/KBS_'24-28a745)](https://doi.org/10.1016/j.knosys.2024.112545) [![GitHub](https://img.shields.io/github/stars/pwy-cmd/AFGCL?style=flat)](https://github.com/pwy-cmd/AFGCL)
* [ ] LookupForensics: A Large-Scale Multi-Task Dataset for Multi-Phase Image-Based Fact Verification [![Static Badge](https://img.shields.io/badge/arXiv_'24-6c757d)](https://arxiv.org/abs/2407.18614)
* [ ] Image manipulation detection and localization using multi-scale contrastive learning [![paper](https://img.shields.io/badge/Appl._Soft_Comput._'24-6c757d)](https://doi.org/10.1016/j.asoc.2024.111914)
* [ ] Attentive and Contrastive Image Manipulation Localization With Boundary Guidance [![paper](https://img.shields.io/badge/TIFS_'24-dc3545)](https://ieeexplore.ieee.org/document/10589438)
* [ ] Rethinking Image Editing Detection in the Era of Generative AI Revolution [![Static Badge](https://img.shields.io/badge/MM_'24-dc3545)](https://arxiv.org/abs/2311.17953) [![GitHub](https://img.shields.io/github/stars/ICTMCG/GRE?style=flat)](https://github.com/ICTMCG/GRE)
* [ ] Multi-view Feature Extraction via Tunable Prompts is Enough for Image Manipulation Localization [![paper](https://img.shields.io/badge/MM_'24-dc3545)](https://openreview.net/forum?id=Ci5g2dnrMK)
* [ ] Datasets, Clues and State-of-the-Arts for Multimedia Forensics: An Extensive Review [![Static Badge](https://img.shields.io/badge/ESWA_'24-28a745)](https://arxiv.org/abs/2401.06999)
* [ ] TGIF: Text-Guided Inpainting Forgery Dataset [![Static Badge](https://img.shields.io/badge/arXiv_'24-6c757d)](http://arxiv.org/abs/2407.11566) [![GitHub](https://img.shields.io/github/stars/IDLabMedia/tgif-dataset?style=flat)](https://github.com/IDLabMedia/tgif-dataset)
* [ ] Exploring Multi-view Pixel Contrast for General and Robust Image Forgery Localization [![Static Badge](https://img.shields.io/badge/TIFS_'25-dc3545)](https://arxiv.org/abs/2406.13565) [![GitHub](https://img.shields.io/github/stars/multimediaFor/MPC?style=flat)](https://github.com/multimediaFor/MPC) _❗Updated_
* [ ] GIM: A Million-scale Benchmark for Generative Image Manipulation Detection and Localization [![Static Badge](https://img.shields.io/badge/arXiv_'24-6c757d)](https://arxiv.org/abs/2406.16531) [![GitHub](https://img.shields.io/github/stars/chenyirui/GIM?style=flat)](https://github.com/chenyirui/GIM)
* [ ] IMDL-BenCo: A Comprehensive Benchmark and Codebase for Image Manipulation Detection & Localization [![Static Badge](https://img.shields.io/badge/NeurIPS_'24-dc3545)](https://arxiv.org/abs/2406.10580) [![GitHub](https://img.shields.io/github/stars/scu-zjz/IMDLBenCo?style=flat)](https://github.com/scu-zjz/IMDLBenCo)
* [ ] DH-GAN: Image manipulation localization via a dual homology-aware generative adversarial network [![Static Badge](https://img.shields.io/badge/PR_'24-ffc107)](https://doi.org/10.1016/j.patcog.2024.110658)
* [ ] DA-HFNet: Progressive Fine-Grained Forgery Image Detection and Localization Based on Dual Attention [![Static Badge](https://img.shields.io/badge/arXiv_'24-6c757d)](http://arxiv.org/abs/2406.01489)
* [ ] EC-Net: General image tampering localization network based on edge distribution guidance and contrastive learning [![Static Badge](https://img.shields.io/badge/KBS_'24-28a745)](https://doi.org/10.1016/j.knosys.2024.111656)
* [ ] Frequency-constrained transferable adversarial attack on image manipulation detection and localization [![Static Badge](https://img.shields.io/badge/TVC_'24-28a745)](https://link.springer.com/article/10.1007/s00371-024-03482-4)
* [ ] A Contribution-Aware Noise Feature representation model for image manipulation localization [![Static Badge](https://img.shields.io/badge/KBS_'24-28a745)](https://doi.org/10.1016/j.knosys.2024.111988)
* [ ] Effective Image Tampering Localization via Enhanced Transformer and Co-attention Fusion [![Static Badge](https://img.shields.io/badge/ICASSP_'24-ffc107)](https://arxiv.org/abs/2309.09306) [![GitHub](https://img.shields.io/github/stars/multimediaFor/EITLNet?style=flat)](https://github.com/multimediaFor/EITLNet)
* [ ] PROMPT-IML: Image Manipulation Localization with Pre-trained Foundation Models Through Prompt Tuning [![Static Badge](https://img.shields.io/badge/arXiv_'24-6c757d)](https://arxiv.org/abs/2401.00653)
* [ ] Diffusion models meet image counter-forensics [![Static Badge](https://img.shields.io/badge/WACV_'24-ffc107)](https://arxiv.org/abs/2311.13629) [![GitHub](https://img.shields.io/github/stars/mtailanian/diff-cf?style=flat)](https://github.com/mtailanian/diff-cf)
* [ ] Research about the Ability of LLM in the Tamper-Detection Area [![Static Badge](https://img.shields.io/badge/arXiv_'24-6c757d)](https://arxiv.org/abs/2401.13504)
* [ ] Deep Image Restoration For Image Anti-Forensics [![Static Badge](https://img.shields.io/badge/arXiv_'24-6c757d)](https://arxiv.org/abs/2405.02751) [![GitHub](https://img.shields.io/github/stars/99eren99/DIRFIAF?style=flat)](https://github.com/99eren99/DIRFIAF)
* [ ] Deep Image Composition Meets Image Forgery [![Static Badge](https://img.shields.io/badge/arXiv_'24-6c757d)](https://arxiv.org/abs/2404.02897) [![GitHub](https://img.shields.io/github/stars/99eren99/DIS25k?style=flat)](https://github.com/99eren99/DIS25k)
* [ ] Fusion Transformer with Object Mask Guidance for Image Forgery Analysis (OMG-Fuser) [![Static Badge](https://img.shields.io/badge/CVPRW_'24-dc3545)](https://arxiv.org/abs/2403.12229) [![GitHub](https://img.shields.io/github/stars/mever-team/omgfuser?style=flat)](https://github.com/mever-team/omgfuser)
* [ ] Exploring Multi-Modal Fusion for Image Manipulation Detection and Localization [![arXiv](https://img.shields.io/badge/MMM_'24-28a745)](https://arxiv.org/abs/2312.01790) [![GitHub](https://img.shields.io/github/stars/idt-iti/mmfusion-iml?style=flat)](https://github.com/idt-iti/mmfusion-iml)
* [ ] A New Benchmark and Model for Challenging Image Manipulation Detection [![arXiv](https://img.shields.io/badge/AAAI_'24-dc3545)](https://arxiv.org/abs/2311.14218) [![GitHub](https://img.shields.io/github/stars/ZhenfeiZ/CIMD?style=flat)](https://github.com/ZhenfeiZ/CIMD)
* [ ] MGQFormer: Mask-Guided Query-Based Transformer for Image Manipulation Localization [![arXiv](https://img.shields.io/badge/AAAI_'24-dc3545)](https://ojs.aaai.org/index.php/AAAI/article/view/28520) [![arXiv](https://img.shields.io/badge/News-4096ff.svg)](https://dml.fudan.edu.cn/d1/65/c35285a643429/page.htm)
* [ ] Learning Discriminative Noise Guidance for Image Forgery Detection and Localization [![arXiv](https://img.shields.io/badge/AAAI_'24-dc3545)](https://ojs.aaai.org/index.php/AAAI/article/view/28608)
* [ ] CatmullRom Splines-Based Regression for Image Forgery Localization [![arXiv](https://img.shields.io/badge/AAAI_'24-dc3545)](https://ojs.aaai.org/index.php/AAAI/article/view/28548)
* [ ] UnionFormer: Unified-Learning Transformer with Multi-View Representation for Image Manipulation Detection and Localization [![arXiv](https://img.shields.io/badge/CVPR_'24-dc3545)](https://openaccess.thecvf.com/content/CVPR2024/papers/Li_UnionFormer_Unified-Learning_Transformer_with_Multi-View_Representation_for_Image_Manipulation_Detection_CVPR_2024_paper.pdf)
* [ ] Towards Modern Image Manipulation Localization: A Large-Scale Dataset and Novel Methods [![arXiv](https://img.shields.io/badge/CVPR_'24-dc3545)](https://openaccess.thecvf.com/content/CVPR2024/papers/Qu_Towards_Modern_Image_Manipulation_Localization_A_Large-Scale_Dataset_and_Novel_CVPR_2024_paper.pdf) [![GitHub](https://img.shields.io/github/stars/qcf-568/MIML?style=flat)](https://github.com/qcf-568/MIML)
* [ ] EditGuard: Versatile Image Watermarking for Tamper Localization and Copyright Protection [![arXiv](https://img.shields.io/badge/CVPR_'24-dc3545)](https://arxiv.org/abs/2312.08883) [![GitHub](https://img.shields.io/github/stars/xuanyuzhang21/EditGuard?style=flat)](https://github.com/xuanyuzhang21/EditGuard)
* [ ] DiffForensics: Leveraging Diffusion Prior to Image Forgery Detection and Localization [![arXiv](https://img.shields.io/badge/CVPR_'24-dc3545)](https://openaccess.thecvf.com/content/CVPR2024/papers/Yu_DiffForensics_Leveraging_Diffusion_Prior_to_Image_Forgery_Detection_and_Localization_CVPR_2024_paper.pdf)
* [ ] IML-ViT: Image Manipulation Localization by Vision Transformer [![arXiv](https://img.shields.io/badge/AAAI_'24-dc3545)](https://arxiv.org/abs/2307.14863) [![GitHub](https://img.shields.io/github/stars/SunnyHaze/IML-ViT?style=flat)](https://github.com/SunnyHaze/IML-ViT)
* [ ] CIMGEN: Controlled Image Manipulation by Finetuning Pretrained Generative Models on Limited Data [![arXiv](https://img.shields.io/badge/arXiv_'24-6c757d)](https://arxiv.org/abs/2401.13006)

</details>

<details>

<summary>2023</summary>

* [ ] Image Manipulation Detection Based on Ringed Residual Edge Artifact Enhancement and Multiple Attention Mechanisms [![Static Badge](https://img.shields.io/badge/PRCV_'24-28a745)](https://link.springer.com/chapter/10.1007/978-981-99-8543-2_30)
* [ ] Improving CoatNet for Spatial and JPEG Domain Steganalysis (_ICME '23_) **\[**[**Paper**](https://ieeexplore.ieee.org/abstract/document/10219598/)**]**
* [ ] A survey on deep learning-based image forgery detection _(PR '23)_ **\[**[**Paper**](https://www.sciencedirect.com/science/article/pii/S0031320323004764)**]**
* [ ] PL-GNet: Pixel Level Global Network for detection and localization of image forgeries [![paper](https://img.shields.io/badge/IMAGE_'23-28a745)](https://www.sciencedirect.com/science/article/pii/S092359652300111X) [![GitHub](https://img.shields.io/github/stars/znshi/PL-GNet?style=flat)](https://github.com/znshi/PL-GNet)
* [ ] Progressive Feedback-Enhanced Transformer for Image Forgery Localization _(arXiv '23)_ **\[**[**Paper**](https://arxiv.org/abs/2311.08910)**]** **\[**[**Code**](https://github.com/multimediaFor/ProFact)**]**
* [ ] Secondary Labeling A Novel Labeling Strategy for Image Manipulation Detection _(MM '23)_ **\[**[**Paper**](https://doi.org/10.1145/3581783.3613839)**]**
* [ ] GP-Net: Image Manipulation Detection and Localization via Long-Range Modeling and Transformers (_Appl. Sci. (IF: 2.8, not included in CCFs), MDPI, '23_) **\[**[**Paper**](https://www.mdpi.com/2076-3417/13/21/12053)**]**
* [ ] DS-Net: Dual supervision neural network for image manipulation localization _(IET-IPR '23)_ **\[**[**Paper**](https://ietresearch.onlinelibrary.wiley.com/doi/abs/10.1049/ipr2.12885)**]**
* [ ] Learning to Immunize Images for Tamper Localization and Self Recovery _(TPAMI ‘23)_ **\[**[**Paper**](https://arxiv.org/pdf/2210.15902.pdf)**]**
* [ ] Semantic-agnostic progressive subtractive network for image manipulation detection and localization _(Neurocomputing '23)_ **\[**[**Paper**](https://doi.org/10.1016/j.neucom.2023.126263)**]**
* [ ] Towards Effective Image Manipulation Detection with Proposal Contrastive Learning _(TCSVT '23)_ **\[**[**Paper**](https://arxiv.org/pdf/2210.08529.pdf)**]** **\[**[**Code**](https://github.com/Sandy-Zeng/PCL)**]**
* [ ] Effective image tampering localization with multi-scale ConvNeXt feature fusion (_JVCIR '23)_ **\[**[**Paper**](https://arxiv.org/abs/2208.13739)**]** **\[**[**Code**](https://github.com/multimediaFor/ConvNeXtFF)**]**
* [ ] Evading Detection Actively: Toward Anti-Forensics against Forgery Localization (_arXiv '23_) **\[**[**Paper**](https://arxiv.org/abs/2310.10036)**]** **\[**[**Code**](https://github.com/tansq/SEAR)**]**
* [ ] [ReLoc: A Restoration-Assisted Framework for Robust Image Tampering Localization](image-forgery/2023/reloc) (_TIFS '23_) **\[**[**Paper**](https://arxiv.org/abs/2211.03930)**]** **\[**[**Code**](https://github.com/ZhuangPeiyu/ReLoc)**]**
* [ ] Image manipulation detection by multiple tampering traces and edge artifact enhancement (_PR '23_) **\[**[**Paper**](https://www.sciencedirect.com/science/article/pii/S0031320322005064)**]** (_EMT-Net_)
* [x] [CFL-Net: Image Forgery Localization Using Contrastive Learning](image-forgery/2023/cfl-net) (_WACV '23_) **\[**[**Paper**](https://arxiv.org/abs/2210.02182)**]** **\[**[**Code**](https://github.com/niloy193/CFLNet)**]**
* [x] [TruFor: Leveraging all-round clues for trustworthy image forgery detection and localization](image-forgery/2023/trufor) (_CVPR '23_) **\[**[**Paper**](https://arxiv.org/abs/2212.10957)**]** **\[**[**Project**](https://grip-unina.github.io/TruFor/)**]** **\[**[**Code**](https://github.com/grip-unina/TruFor)**]**
* [x] [TBFormer: Two-Branch Transformer for Image Forgery Localization](image-forgery/2023/tbformer) (_SPL '23_) **\[**[**Paper**](https://arxiv.org/abs/2302.13004)**]** **\[**[**Code**](https://github.com/free1dom1/tbformer)**]**
* [ ] [Detecting and Grounding Multi-Modal Media Manipulation](image-forgery/2023/dgm4) (_CVPR '23_) **\[**[**Paper**](https://arxiv.org/abs/2304.02556)**]** **\[**[**Code**](https://github.com/rshaojimmy/MultiModal-DeepFake)**]** **\[**[**Project**](https://rshaojimmy.github.io/Projects/MultiModal-DeepFake)**]**
* [x] [Hierarchical Fine-Grained Image Forgery Detection and Localization](image-forgery/2023/hifi_ifdl) (_CVPR '23_) **\[**[**Paper**](https://arxiv.org/abs/2303.17111)**]** **\[**[**Code**](https://github.com/CHELSEA234/HiFi_IFDL)**]**
* [ ] [Edge-aware Regional Message Passing Controller for Image Forgery Localization](image-forgery/2023/ermpc) (_CVPR '23_) **\[**[**Paper**](https://openaccess.thecvf.com/content/CVPR2023/papers/Li_Edge-Aware_Regional_Message_Passing_Controller_for_Image_Forgery_Localization_CVPR_2023_paper.pdf)**]** **\[**[**Video**](https://youtu.be/2pDR-hOFcQw)**]**
* [ ] AutoSplice: A Text-prompt Manipulated Image Dataset for Media Forensics (_CVPRW '23_) **\[**[**Paper**](https://arxiv.org/abs/2304.06870)**]** **\[**[**Dataset**](https://github.com/shanface33/autosplice_dataset)**]**
* [ ] TrainFors: A Large Benchmark Training Dataset for Image Manipulation Detection and Localization (_ICCV '23_) **\[**[**Paper**](https://arxiv.org/abs/2308.05264)**]** **\[**[**Code**](https://github.com/vimal-isi-edu/TrainFors)**]**
* [ ] Pre-training-free Image Manipulation Localization through Non-Mutually Exclusive Contrastive Learning (_ICCV '23_) **\[**[**Paper**](https://openaccess.thecvf.com/content/ICCV2023/html/Zhou_Pre-Training-Free_Image_Manipulation_Localization_through_Non-Mutually_Exclusive_Contrastive_Learning_ICCV_2023_paper.html)**]** **\[**[**Code**](https://github.com/Knightzjz/NCL-IML)**]**
* [ ] Towards Generic Image Manipulation Detection with Weakly-Supervised Self-Consistency Learning (_ICCV '23_) **\[**[**Paper**](https://openaccess.thecvf.com/content/ICCV2023/html/Zhai_Towards_Generic_Image_Manipulation_Detection_with_Weakly-Supervised_Self-Consistency_Learning_ICCV_2023_paper.html)**]** **\[**[**Code**](https://github.com/yhZhai/WSCL)**]** **\[**[**ResearchGate**](https://www.researchgate.net/publication/373686108_Towards_Generic_Image_Manipulation_Detection_with_Weakly-Supervised_Self-Consistency_Learning)**]**
* [ ] SAFL-Net: Semantic-Agnostic Feature Learning Network with Auxiliary Plugins for Image Manipulation Detection (_ICCV '23_) **\[**[**Paper**](https://openaccess.thecvf.com/content/ICCV2023/html/Sun_SAFL-Net_Semantic-Agnostic_Feature_Learning_Network_with_Auxiliary_Plugins_for_Image_ICCV_2023_paper.html)**]**
* [ ] Uncertainty-guided Learning for Improving Image Manipulation Detection (_ICCV '23_) **\[**[**Paper**](https://openaccess.thecvf.com/content/ICCV2023/html/Ji_Uncertainty-guided_Learning_for_Improving_Image_Manipulation_Detection_ICCV_2023_paper.html)**]**
* [ ] Rethinking Image Forgery Detection via Contrastive Learning and Unsupervised Clustering (_arXiv '23_) **\[**[**Paper**](https://arxiv.org/abs/2308.09307)**]** **\[**[**Code**](https://github.com/HighwayWu/FOCAL)**]**
* [ ] Pixel-Inconsistency Modeling for Image Manipulation Localization (_arXiv '23_) **\[**[**Paper**](https://arxiv.org/abs/2310.00234)**]** [![paper](https://img.shields.io/badge/TPAMI_'25-dc3545)](https://ieeexplore.ieee.org/abstract/document/10883001/) [![GitHub](https://img.shields.io/github/stars/ChenqiKONG/PIM?style=flat)](https://github.com/ChenqiKONG/PIM)_❗Updated_
* [ ] Perceptual MAE for Image Manipulation Localization: A High-level Vision Learner Focusing on Low-level Features (_arXiv '23_) **\[**[**Paper**](https://arxiv.org/abs/2310.06525)**]**
* [ ] [On the Security of the One-and-a-Half-Class Classifier for SPAM Feature-Based Image Forensics](https://github.com/greatzh/Papers/blob/main/image-forgery/2023/spam_analysis.md) (_TIFS '23_) **(Traditional method, Analysis)** **\[**[**Paper**](https://ieeexplore.ieee.org/abstract/document/10098583/)**]**

</details>

<details>

<summary>2022</summary>

* [ ] DS-UNet: A dual streams UNet for refined image forgery localization _(InfoS '22)_ **\[**[**Paper**](https://dl.acm.org/doi/abs/10.1016/j.ins.2022.08.005)**]**
* [ ] MSMG-Net: Multi-scale Multi-grained Supervised Metworks for Multi-task Image Manipulation Detection and Localization (_ArXiv '22_) **\[**[**Paper**](https://arxiv.org/abs/2211.03140)**]**
* [ ] Towards JPEG-Resistant Image Forgery Detection and Localization Via Self-Supervised Domain Adaptation (_TPAMI '22_) **\[**[**Paper**](https://ieeexplore.ieee.org/document/9904872)**]**
* [ ] ESRNet: Efficient Search and Recognition Network for Image Manipulation Detection (_TOMCCAP '22_) **\[**[**Paper**](https://doi.org/10.1145/3506853)**]** **\[**[**Tool**](https://github.com/tampered816/rrr)**]**
* [ ] Learning to localize image forgery using end-to-end attention network (_Neurocomputing '22_) **\[**[**Paper**](https://www.sciencedirect.com/science/article/pii/S0925231222011274)**]** **\[**[**Code**](https://github.com/sadaf-ali/-Learning-to-Localize-Image-Forgery-Using-End-to-End-Attention-Network)**]**
* [ ] MVSS-Net: Multi-View Multi-Scale Supervised Networks for Image Manipulation Detection (_TPAMI '22_) **\[**[**Paper**](https://arxiv.org/abs/2112.08935)**]** **\[**[**Code**](https://github.com/dong03/MVSS-Net)**]**
* [ ] [Robust Image Forgery Detection Over Online Social Network Shared Images](image-forgery/2022/ifosn) (_CVPR '22_) **\[**[**Paper**](https://openaccess.thecvf.com/content/CVPR2022/papers/Wu_Robust_Image_Forgery_Detection_Over_Online_Social_Network_Shared_Images_CVPR_2022_paper.pdf)**]** **\[**[**Code**](https://github.com/HighwayWu/ImageForensicsOSN)**]**
* [x] [ObjectFormer for Image Manipulation Detection and Localization](image-forgery/2022/objectformer) (_CVPR '22_) **\[**[**Paper**](https://arxiv.org/abs/2203.14681)**]**
* [ ] GCA-Net: Utilizing Gated Context Attention for Improving Image Forgery Localization and Detection (_CVPRW '22_) **\[**[**Paper**](https://arxiv.org/abs/2112.04298)**]**
* [ ] Non-Semantic Evaluation of Image Forensics Tools: Methodology and Database (_WACV '22_) **\[**[**Paper**](https://arxiv.org/abs/2105.02700)**]** **\[**[**Code**](https://github.com/qbammey/trace)**]**
* [ ] [JPEG Compression-aware Image Forgery Localization](image-forgery/2022/caifl) (_MM '22_) **\[**[**Paper**](https://dl.acm.org/doi/abs/10.1145/3503161.3547749)**]**
* [ ] [Image Manipulation Localization Using Multi-Scale Feature Fusion and Adaptive Edge Supervision](image-forgery/2022/msff) (_TMM '22_) **\[**[**Paper**](https://ieeexplore.ieee.org/document/9996125/)**]**
* [x] [PSCC-Net: Progressive Spatio-Channel Correlation Network for Image Manipulation Detection and Localization](image-forgery/2022/pscc-net) (_TCSVT '22_) **\[**[**Paper**](https://arxiv.org/abs/2103.10596)**]** **\[**[**Code**](https://github.com/proteus1991/PSCC-Net)**]**
* [x] [Self-Adversarial Training incorporating Forgery Attention for Image Forgery Localization](image-forgery/2022/satfl) (_TIFS '22_) **\[**[**Paper**](https://arxiv.org/abs/2107.02434)**]** **\[**[**Code**](https://github.com/tansq/SATFL)**]** (_LocateNet / SATFL_)
* [ ] M2TR: Multi-modal Multi-scale Transformers for Deepfake Detection (_ICMR '22_) **\[**[**Paper**](https://arxiv.org/abs/2104.09770)**]** **\[**[**Code**](https://github.com/wangjk666/M2TR-Multi-modal-Multi-scale-Transformers-for-Deepfake-Detection)**]**
* [ ] A Principled Design of Image Representation: Towards Forensic Tasks (_TPAMI '22_) **\[**[**Paper**](https://arxiv.org/abs/2203.00913)**]** **\[**[**Code**](https://github.com/ShurenQi/DIR)**]**
* [ ] [TBNet: A Two-stream Boundary-aware Network for Generic Image Manipulation Localization](image-forgery/2022/tbanet) (_KDE '22_) **\[**[**Paper**](https://arxiv.org/abs/2108.04508)**]**
* [ ] [Learning JPEG Compression Artifacts for Image Manipulation Detection and Localization](image-forgery/2022/catnetv2) (_IJCV '22_) **\[**[**Paper**](https://arxiv.org/abs/2108.12947)**]** **\[**[**Code**](https://github.com/mjkwon2021/CAT-Net)**]**
* [ ] Fighting Malicious Media Data: A Survey on Tampering Detection and Deepfake Detection (_arXiv '22_) (**Survey**) **\[**[**Paper**](https://arxiv.org/abs/2212.05667)**]**
* [ ] Generic Image Manipulation Localization through the Lens of Multi-scale Spatial Inconsistence _(MM '22)_ **\[**[**Paper**](http://dl.acm.org/citation.cfm?id=3548100)**]**

</details>

<details>

<summary>2021</summary>

* [ ] Multi-modality image manipulation detection (_ICME '21_) **\[**[**Paper**](https://doi.org/10.1109/ICME51207.2021.9428232)**]**
* [ ] MSTA-Net: Forgery Detection by Generating Manipulation Trace Based on Multi-Scale Self-Texture Attention (_TCSVT '21_) **\[**[**Paper**](https://ieeexplore.ieee.org/document/9643421)**]**
* [ ] Image Manipulation Detection by Multi-View Multi-Scale Supervision (_ICCV '21_) **\[**[**Paper**](https://arxiv.org/abs/2104.06832)**]** **\[**[**Code**](https://github.com/dong03/MVSS-Net)**]**
* [x] [TransForensics: Image Forgery Localization with Dense Self-Attention](image-forgery/2021/transforensics) (_ICCV '21_) **\[**[**Paper**](https://arxiv.org/abs/2108.03871)**]**
* [ ] Self-supervised Domain Adaptation for Forgery Localization of JPEG Compressed Images (_ICCV '21_) **\[**[**Paper**](https://openaccess.thecvf.com/content/ICCV2021/html/Rao_Self-Supervised_Domain_Adaptation_for_Forgery_Localization_of_JPEG_Compressed_Images_ICCV_2021_paper.html)**]**
* [ ] Image Tampering Localization Using a Dense Fully Convolutional Network (_TIFS '21_) **\[**[**Paper**](https://ieeexplore.ieee.org/document/9393396)**]** **\[**[**Code**](https://github.com/ZhuangPeiyu/Dense-FCN-for-tampering-localization)**]** (_DenseFCN_)
* [ ] Image Manipulation Localization Using Attentional Cross-Domain CNN Features (_TNNLS '21_) **\[**[**Paper**](https://doi.org/10.1109/TNNLS.2021.3130168)**]**

</details>

<details>

<summary>2020 and before</summary>

* [ ] A Full-Image Full-Resolution End-to-EndTrainable CNN Framework for Image Forgery Detection (_IEEE Access '20_) \*\*\[[Paper](readme)]
* [ ] ![ConfnPubs](https://img.shields.io/badge/ICME-'20-ffc53d.svg)Constrained R-CNN: A general image manipulation detection model **\[**[**Paper**](https://arxiv.org/abs/1911.08217)**]** **\[**[**Code**](https://github.com/VedantWani/Constrained-R-CNN)**]**
* [ ] A CNNBased Camera Model Fingerprint (_TIFS '20_) \*\*\[[Paper](readme)]
* [ ] An Adaptive Neural Network for Unsupervised Mosaic Consistency Analysis in Image Forensics (_CVPR '20_) **\[**[**Paper**](http://openaccess.thecvf.com/content_CVPR_2020/html/Bammey_An_Adaptive_Neural_Network_for_Unsupervised_Mosaic_Consistency_Analysis_in_CVPR_2020_paper.html)**]** **\[**[**Code**](https://github.com/qbammey/adaptive_cfa_forensics)**]**
* [ ] A dense u-net with cross-layer intersection for detection and localization of image forgery (_ICASSP '20_) **\[**[**Paper**](https://ieeexplore.ieee.org/document/9054068)**]** **\[**[**Note\_unofficial**](https://blog.csdn.net/weixin_45366180/article/details/128413821)**]**
* [x] [Generate, Segment, and Refine: Towards Generic Manipulation Segmentation](image-forgery/2020/gsrnet) (_AAAI '20_) **\[**[**Paper**](https://arxiv.org/abs/1811.09729)**]** **\[**[**Code**](https://github.com/pengzhou1108/GSRNet)**]** (_GSRNet_)
* [ ] SPAN: Spatial Pyramid Attention Network for Image Manipulation Localization (_ECCV '20_) **\[**[**Paper**](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123660307.pdf)**]** **\[**[**Code**](https://github.com/tsaishien-chen/SPAN)**]** [![GitHub Page](https://img.shields.io/badge/Project-Page-159957.svg)](http://media.ee.ntu.edu.tw/research/SPAN/)
* [ ] [Hybrid LSTM and Encoder-Decoder Architecture for Detection of Image Forgeries](image-forgery/2019/hled) (_TIP '19_) **\[**[**Paper**](https://arxiv.org/abs/1903.02495)**]** **\[**[**Code**](https://github.com/jawadbappy/forgery_localization_HLED)**]**
* [ ] ManTra-Net: Manipulation Tracing Network for Detection and Localization of Image Forgeries With Anomalous Features (_CVPR '19_) **\[**[**Paper**](https://ieeexplore.ieee.org/document/8953774)**]** **\[**[**Code**](https://github.com/ISICV/ManTraNet)**]**
* [ ] Learning Rich Features for Image Manipulation Detection (_CVPR '18_) **\[**[**Paper**](https://arxiv.org/abs/1805.04953)**]** **\[**[**Code**](https://github.com/LarryJiang134/Image_manipulation_detection)**]**

</details>

#### CNN-synthesized

_Some of the above papers also contain methods to detect tampered images generated by GANs or DMs or **LLMs related** for synthetic images_

* [ ] _Frequency_-_aware Correlation Discovering_ and Spatial Forgery Clue Distilling for Synthetic Image Detection [![paper](https://img.shields.io/badge/MM_'25-dc3545)](readme)
* [ ] ForgeLens: Data-Efficient Forgery Focus for Generalizable Forgery Image Detection [![paper](https://img.shields.io/badge/ICCV_'25-dc3545)](https://arxiv.org/abs/2408.13697) [![GitHub](https://img.shields.io/github/stars/Yingjian-Chen/ForgeLens?style=flat)](https://github.com/Yingjian-Chen/ForgeLens)
* [ ] ImgEdit: A Unified Image Editing Dataset and Benchmark [![Static Badge](https://img.shields.io/badge/arXiv_'25-6c757d)](https://arxiv.org/abs/2505.20275) [![GitHub](https://img.shields.io/github/stars/PKU-YuanGroup/ImgEdit?style=flat)](https://github.com/PKU-YuanGroup/ImgEdit)
* [ ] Orthogonal Subspace Decomposition for Generalizable AI-Generated Image Detection [![paper](https://img.shields.io/badge/ICML_'25-dc3545)](https://arxiv.org/abs/2411.15633) [![GitHub](https://img.shields.io/github/stars/YZY-stack/Effort-AIGI-Detection?style=flat)](https://github.com/YZY-stack/Effort-AIGI-Detection)
* [ ] MFF-Net: A multi-view feature fusion network for generalized forgery image detection [![Static Badge](https://img.shields.io/badge/Neurocomputing_'25-28a745)](https://www.sciencedirect.com/science/article/pii/S0925231225010239) [![GitHub](https://img.shields.io/github/stars/DragonM096/MFF-Net?style=flat)](https://github.com/DragonM096/MFF-Net/)
* [ ] STD-FD: Spatio-Temporal Distribution Fitting Deviation for AIGC Forgery Identification [![paper](https://img.shields.io/badge/ICML_'25-dc3545)](https://icml.cc/virtual/2025/poster/45231)
* [ ] So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection [![Static Badge](https://img.shields.io/badge/arXiv_'25-6c757d)](https://arxiv.org/abs/2505.18660) [![GitHub](https://img.shields.io/github/stars/hzlsaber/So-Fake?style=flat)](https://github.com/hzlsaber/So-Fake/)
* [ ] Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective [![Static Badge](https://img.shields.io/badge/arXiv_'25-6c757d)](https://arxiv.org/abs/2505.22604)
* [ ] Spatial-Temporal Reconstruction Error for AIGC-based Forgery Image Detection [![Static Badge](https://img.shields.io/badge/ICASSP_'25-ffc107)](https://ieeexplore.ieee.org/abstract/document/10890455)
* [ ] Noise-Informed Diffusion-Generated Image Detection With Anomaly Attention [![Static Badge](https://img.shields.io/badge/TIFS_'25-dc3545)](https://ieeexplore.ieee.org/abstract/document/11018089)
* [ ] FAMSeC: A Few-Shot-Sample-Based General AI-Generated Image Detection Method [![Static Badge](https://img.shields.io/badge/SPL_'25-28a745)](https://ieeexplore.ieee.org/abstract/document/10777302)
* [ ] FakeScope: Large Multimodal Expert Model for Transparent AI-Generated Image Forensics [![Static Badge](https://img.shields.io/badge/arXiv_'25-6c757d)](https://arxiv.org/abs/2503.24267) [![GitHub](https://img.shields.io/github/stars/Yixuan423/FakeScope?style=flat)](https://github.com/Yixuan423/FakeScope)
* [ ] Exploring the Collaborative Advantage of Low-level Information on Generalizable AI-Generated Image Detection [![Static Badge](https://img.shields.io/badge/arXiv_'25-6c757d)](https://arxiv.org/abs/2504.00463)
* [ ] AnimeDL-2M: Million-Scale AI-Generated Anime Image Detection and Localization in Diffusion Era [![Static Badge](https://img.shields.io/badge/arXiv_'25-6c757d)](https://arxiv.org/abs/2504.11015) [![GitHub](https://img.shields.io/github/stars/FlyTweety/AnimeDL2M?style=flat)](https://github.com/FlyTweety/AnimeDL2M)
* [ ] Can GPT tell us why these images are synthesized? Empowering Multimodal Large Language Models for Forensics [![Static Badge](https://img.shields.io/badge/arXiv_'25-6c757d)](https://arxiv.org/abs/2504.11686)
* [ ] Zooming In on Fakes: A Novel Dataset for Localized AI-Generated Image Detection with Forgery Amplification Approach [![Static Badge](https://img.shields.io/badge/arXiv_'25-6c757d)](https://arxiv.org/abs/2504.11922) [![GitHub](https://img.shields.io/github/stars/clpbc/BR-Gen?style=flat)](https://github.com/clpbc/BR-Gen)
* [ ] FakeReasoning: Towards Generalizable Forgery Detection and Reasoning [![Static Badge](https://img.shields.io/badge/arXiv_'25-6c757d)](https://arxiv.org/abs/2503.21210)
* [ ] Spot the Fake: Large Multimodal Model-Based Synthetic Image Detection with Artifact Explanation [![Static Badge](https://img.shields.io/badge/arXiv_'25-6c757d)](http://arxiv.org/abs/2503.14905) [![GitHub](https://img.shields.io/github/stars/opendatalab/FakeVLM?style=flat)](https://github.com/opendatalab/FakeVLM)
* [ ] LEGION: Learning to Ground and Explain for Synthetic Image Detection [![Static Badge](https://img.shields.io/badge/arXiv_'25-6c757d)](https://arxiv.org/abs/2503.15264) [![GitHub](https://img.shields.io/github/stars/opendatalab/LEGION?style=flat)](https://github.com/opendatalab/LEGION)
* [ ] Survey on AI-Generated Media Detection: From Non-MLLM to MLLM [![Static Badge](https://img.shields.io/badge/arXiv_'25-6c757d)](https://arxiv.org/abs/2502.05240)
* [ ] A Sanity Check for AI-generated Image Detection [![Static Badge](https://img.shields.io/badge/ICLR_'25-6c757d)](https://arxiv.org/abs/2406.19435) [![GitHub](https://img.shields.io/github/stars/shilinyan99/AIDE?style=flat)](https://github.com/shilinyan99/AIDE)
* [ ] MMFakeBench: A Mixed-Source Multimodal Misinformation Detection Benchmark for LVLMs [![Static Badge](https://img.shields.io/badge/ICLR_'25-6c757d)](https://openreview.net/forum?id=D6zn6ozJs7)
* [ ] Forgery-aware Adaptive Transformer for Generalizable Synthetic Image Detection _(CVPR '24)_ **\[**[**Paper**](https://arxiv.org/abs/2312.16649)**]**
* [ ] Preserving Fairness Generalization in Deepfake Detection _(CVPR '24)_ **\[**[**Paper**](https://arxiv.org/abs/2402.17229)**]** **\[**[**Code**](https://github.com/Purdue-M2/Fairness-Generalization)**]**
* [ ] Leveraging Representations from Intermediate Encoder-blocks for Synthetic Image Detection _(ECCV '24)_ **\[**[**Paper**](https://arxiv.org/abs/2402.19091)**]** **\[**[**Code**](https://github.com/mever-team/rine)**]**
* [ ] Forgery-aware Adaptive Transformer for Generalizable Synthetic Image Detection _(arXiv '23)_ **\[**[**Paper**](https://arxiv.org/abs/2312.16649)**]**
* [ ] AntifakePrompt: Prompt-Tuned Vision-Language Models are Fake Image Detectors (_arXiv '23_) **\[**[**Paper**](https://arxiv.org/abs/2310.17419)**]** **\[**[**Code**](https://github.com/nctu-eva-lab/AntifakePrompt)**]**
* [ ] MaLP: Manipulation Localization Using a Proactive Scheme (_CVPR '23_) **\[**[**Paper**](https://arxiv.org/abs/2303.16976)**]** **\[**[**Code**](https://github.com/vishal3477/pro_loc)**]**
* [ ] Discrepancy-Guided Reconstruction Learning for Image Forgery Detection (_IJCAI '23_) **\[**[**Paper**](https://arxiv.org/abs/2304.13349)**]** **\[**[**Code**](https://github.com/znshi/DisGRL)**]**
* [ ] Generalizable Synthetic Image Detection via Language-guided Contrastive Learning (_arXiv '23_) **\[**[**Paper**](https://arxiv.org/abs/2305.13800)**]** **\[**[**Code**](https://github.com/HighwayWu/LASTED)**]**
* [ ] Detect Any Deepfakes: Segment Anything Meets Face Forgery Detection and Localization (_arXiv '23_) **\[**[**Paper**](https://arxiv.org/abs/2306.17075)**]** **\[**[**Code**](https://github.com/laiyingxin2/DADF)**]**
* [ ] Discrepancy-Guided Reconstruction Learning for Image Forgery Detection (_arXiv '23_) **\[**[**Paper**](https://arxiv.org/abs/2304.13349)**]**
* [ ] Masked Relation Learning for DeepFake Detection (_TIFS '23_) **\[**[**Paper**](https://doi.org/10.1109/TIFS.2023.3249566)**]**

### Image Splicing

**图像的拼接篡改检测定位**

* [ ] Image splicing localization method driven by device difference feature guidance [![Static Badge](https://img.shields.io/badge/PR_'25-ffc107)](https://doi.org/10.1016/j.patcog.2025.112002)

<details>

<summary>2024</summary>

* [ ] Image splicing forgery detection: A review [![Static Badge](https://img.shields.io/badge/MTA_'24-28a745)](https://link.springer.com/article/10.1007/s11042-024-18801-z)
* [ ] Multi-Scale Cross-Fusion and Edge-Supervision Network for Image Splicing Localization [![Static Badge](https://img.shields.io/badge/arXiv_'24-6c757d)](https://arxiv.org/abs/2412.12503)
* [ ] D-Net: A dual-encoder network for image splicing forgery detection and localization [![Static Badge](https://img.shields.io/badge/PR_'24-ffc107)](https://arxiv.org/abs/2012.01821)
* [ ] UGEE-Net: Uncertainty-Guided and Edge-Enhanced Network for Image Splicing Localization (_Neural Networks '24_) **\[**[**Paper**](https://doi.org/10.1016/j.neunet.2024.106430)**]** **\[**[**Dataset**](https://github.com/QixianHao/-HTSI12K-dataset)**]**
* [ ] Research on Splicing Image Detection Algorithms Based on Natural Image Statistical Characteristics (_arXiv '24_) **\[**[**Paper**](https://arxiv.org/abs/2404.16296)**]**
* [ ] A Visually Attentive Splice Localization Network with Multi-Domain Feature Extractor and Multi-Receptive Field Upsampler (_arXiv '24_) **\[**[**Paper**](https://arxiv.org/abs/2401.06995)**]**
* [ ] Feature Aggregation and Region-Aware Learning for Detection of Splicing Forgery _(SPL '24)_ **\[**[**Paper**](https://ieeexplore.ieee.org/abstract/document/10378732/)**]**
* [ ] Towards Effective Image Forensics via A Novel Computationally Efficient Framework and A New Image Splice Dataset _( Signal, Image and Video Processing (IF: 2.3, not included in CCFs), '24 )_ **\[**[**Paper**](https://arxiv.org/abs/2401.06998)**]**

</details>

<details>

<summary>2023</summary>

* [ ] GreatSplicing: A Semantically Rich Splicing Dataset _(arXiv '23)_ **\[**[**Paper**](https://arxiv.org/abs/2310.10070)**]** **\[**[**Dataset**](http://www.greatsplicing.net/)**]**
* [ ] Multi-scale attention context-aware network for detection and localization of image splicing: Efficient and robust identification network _(Appl. Intell. 23')_ **\[**[**Paper**](https://link.springer.com/article/10.1007/s10489-022-04421-3)**]**
* [ ] A Multi-Stream Fusion Network for Image Splicing Localization _(MMM '23)_ **\[**[**Paper**](https://arxiv.org/abs/2212.01128)**]**
* [ ] Attacking Image Splicing Detection and Localization Algorithms Using Synthetic Traces _(TIFS '23)_ **\[**[**Paper**](https://arxiv.org/abs/2211.12314)**]** **\[**[**IEEE Paper**](https://doi.org/10.1109/TIFS.2023.3346312)**]**
* [ ] Biomedical Image Splicing Detection using Uncertainty-Guided Refinement _(arXiv '23)_ **\[**[**Paper**](https://arxiv.org/abs/2309.16388)**]**
* [ ] A New Method to Detect Splicing Image Forgery Using Convolutional Neural Network (_Applied Science (IF: 2.8, not included in CCFs), MDPI, '23_) **\[**[**Paper**](https://www.mdpi.com/2076-3417/13/3/1272)**]**
* [ ] Multi-scale Target-Aware Framework for Constrained Image Splicing Detection and Localization (_MM '23_) **\[**[**Paper**](https://arxiv.org/abs/2308.09357)**]**

</details>

<details>

<summary>2022</summary>

* [x] [Multi-Task SE-Network for Image Splicing Localization](image-splicing/multi-task-se-network) (_TCSVT '22_) **\[**[**Paper**](https://ieeexplore.ieee.org/document/9591639)**]** **\[**[**Code**](https://github.com/YulansZhang/Multi-task-SE-Network-for-Image-Splicing-Localization)**]**
* [x] [ET: Edge-Enhanced Transformer for Image Splicing Detection](image-splicing/et) (_SPL '22_) **\[**[**Paper**](https://ieeexplore.ieee.org/document/9769936)**]**
* [x] [Image splicing forgery detection by combining synthetic adversarial networks and hybrid dense U-net based on multiple spaces](image-splicing/san-and-hdu-net) (_IJIS '22_) **\[**[**Paper**](https://doi.org/10.1002/int.22939)**]** **\[**[**Code**](https://github.com/yelusaleng/SAN_and_HDU-Net)**]**
* [x] [SISL:Self-Supervised Image Signature Learning for Splicing Detection & Localization](image-splicing/sisl) (_CVPRW '22_) **\[**[**Paper**](https://arxiv.org/abs/2203.07824)**]**
* [ ] Deep Metric Color Embeddings for Splicing Localization in Severely Degraded Images (_TIFS '22_) **\[**[**Paper**](https://arxiv.org/abs/2206.10737)**]**
* [ ] Coarse-to-fine-grained method for image splicing region detection (_PR '22_) **\[**[**Paper**](https://doi.org/10.1016/j.patcog.2021.108347)**]**

</details>

<details>

<summary>2021</summary>

* [x] [CAT-Net: Compression Artifact Tracing Network for Detection and Localization of Image Splicing](image-splicing/cat-net) (_WACV '21_) **\[**[**Paper**](https://ieeexplore.ieee.org/document/9423390)**]** **\[**[**Code**](https://github.com/mjkwon2021/CAT-Net)**]**
* [ ] Image Splicing Detection, Localization and Attribution via JPEG Primary Quantization Matrix Estimation and Clustering (_TIFS '21_) **\[**[**Paper**](https://ieeexplore.ieee.org/document/9622213)**]** **\[**[**Code**](https://github.com/andreacos/CnnJpegPrimaryQuantizationEstimation)**]**
* [ ] Multiple Image Splicing Dataset (MISD): A Dataset for Multiple Splicing (_Data, MDPI '21_) **\[**[**Paper**](https://arxiv.org/abs/2108.09674)**]**
* [ ] Reality Transform Adversarial Generators for Image Splicing Forgery Detection and Localization (_ICCV '21_) **\[**[**Paper**](http://openaccess.thecvf.com/content/ICCV2021/html/Bi_Reality_Transform_Adversarial_Generators_for_Image_Splicing_Forgery_Detection_and_ICCV_2021_paper.html)**]**
* [x] [Multi-Task Wavelet Corrected Network for Image Splicing Forgery Detection and Localization](image-splicing/mwc-net) (_ICME '21_) **\[**[**Paper**](https://ieeexplore.ieee.org/abstract/document/9428466/)**]**
* [ ] Detection and Localization of Multiple Image Splicing Using MobileNet V1 (_IEEE Access '21_) **\[**[**Paper**](https://arxiv.org/abs/2108.09674)**]**

</details>

<details>

<summary>2020 and before</summary>

* [ ] D-Unet: A Dual-encoder U-Net for Image Splicing Forgery Detection and Localization _(arXiv '20)_ **\[**[**Paper**](https://arxiv.org/abs/2012.01821)**]**
* [ ] Exposing splicing forgery in realistic scenes using deep fusion network (_InfoS '20_) **\[**[**Paper**](https://www.sciencedirect.com/science/article/pii/S0020025520302796)**]**
* [ ] Locating splicing forgery by adaptive-SVD noise estimation and vicinity noise descriptor (_Neurocomputing '20_) **\[**[**Paper**](https://www.sciencedirect.com/science/article/abs/pii/S0925231220300278)**]**
* [ ] Adversarial Learning for Constrained Image Splicing Detection and Localization Based on Atrous Convolution (_TIFS '19_) **\[**[**Paper**](https://ieeexplore.ieee.org/document/8658131)**]** **\[**[**Code**](https://github.com/yaqiliu-cs/CISDL-DMAC)**]**
* [ ] [RRU-Net: The Ringed Residual U-Net for Image Splicing Forgery Detection](image-splicing/rru-net) (_CVPRW' 19_) **\[**[**Paper**](http://openaccess.thecvf.com/content_CVPRW_2019/html/CV-COPS/Bi_RRU-Net_The_Ringed_Residual_U-Net_for_Image_Splicing_Forgery_Detection_CVPRW_2019_paper.html?ref=https://githubhelp.com)**]** **\[**[**Code**](https://github.com/yelusaleng/RRU-Net)**]**
* [ ] Mixed adversarial generators for image splice detection (_NeuIPS '19_) **\[**[**Paper**](https://papers.nips.cc/paper/8315-the-point-where-reality-meets-fantasy-mixed-adversarial-generators-for-image-splice-detection)**]** **\[**[**Code**](https://github.com/vlkniaz/MAGritte)**]**
* [ ] Image Splicing Localization via Semi-global Network and Fully Connected Conditional Random Fields (_ECCV '18_)
* [ ] Image splicing localization using a multi-task fully convolutional network (mfcn) (_JVCIR '18_) **\[**[**Paper**](https://arxiv.org/abs/1709.02016)**]** **\[**[**Code**](https://github.com/namtpham/image_tampering_detection_references.git)**]**
* [x] [Fighting Fake News: Image Splice Detection via Learned Self-Consistency](image-splicing/self-consistency) (_ECCV '18_) **\[**[**Paper**](https://openaccess.thecvf.com/content_ECCV_2018/html/Jacob_Huh_Fighting_Fake_News_ECCV_2018_paper.html)**]** **\[**[**Code**](https://github.com/minyoungg/selfconsistency)**]**
* [ ] Deep Fusion Network for Splicing Forgery Localization (_ECCV '18_)
* [ ] Deep matching and validation network: An end-to-end solution to constrained image splicing localization and detection (_MM '17_) **\[**[**Paper**](https://arxiv.org/abs/1705.09765)**]**

</details>

### Image Harmonization

**图像协调化**

* [ ] Toward Realistic Image Compositing with Adversarial Learning (_CVPR '19_) **\[**[**Paper**](http://openaccess.thecvf.com/content_CVPR_2019/html/Chen_Toward_Realistic_Image_Compositing_With_Adversarial_Learning_CVPR_2019_paper.html)**]** **\[**[**Code\_unofficial**](https://github.com/SuhyeonHa/GCC-GANs)**]**
* [x] [Image Harmonization with Transformer](image-harmonization/ht-d-ht) (_ICCV '21_) **\[**[**Paper**](http://openaccess.thecvf.com/content/ICCV2021/html/Guo_Image_Harmonization_With_Transformer_ICCV_2021_paper.html)**]**
* [ ] SSH: A Self-Supervised Framework for Image Harmonization (_ICCV '21_) **\[**[**Paper**](https://arxiv.org/abs/2108.06805)**]** **\[**[**Code**](https://github.com/VITA-Group/SSHarmonization)**]**
* [ ] Image Harmonization with Region-wise Contrastive Learning (_ArXiv '22_) **\[**[**Paper**](https://arxiv.org/abs/2205.14058)**]**
* [ ] [Harmonizer: Learning to Perform White-Box Image and Video Harmonization](image-harmonization/harmonizer) (_ECCV '22_) **\[**[**Paper**](https://arxiv.org/abs/2207.01322)**]** **\[**[**Code**](https://github.com/ZHKKKe/Harmonizer)**]**
* [ ] Spatial-Separated Curve Rendering Network for Efficient and High-Resolution Image Harmonization (_ECCV '22_) **\[**[**Paper**](https://arxiv.org/abs/2109.05750)**]** **\[**[**Code**](https://github.com/stefanLeong/S2CRNet)**]**
* [ ] High-Resolution Image Harmonization via Collaborative Dual Transformations (_CVPR '22_) **\[**[**Paper**](https://arxiv.org/abs/2109.06671)**]** **\[**[**Code\_unofficial**](https://github.com/SuhyeonHa/CDTNet-PyTorch)**]**
* [ ] [SCS-Co: Self-Consistent Style Contrastive Learning for Image Harmonization](image-harmonization/scs-co) (_CVPR '22_) **\[**[**Paper**](https://arxiv.org/abs/2204.13962)**]** **\[**[**Code**](https://github.com/YCHang686/SCS-Co-CVPR2022)**]**
* [ ] PCT-Net: Full Resolution Image Harmonization Using Pixel-Wise Color Transformations (_CVPR '23_)
* [ ] Semi-supervised Parametric Real-world Image Harmonization (_CVPR '23_) **\[**[**Paper**](https://arxiv.org/abs/2303.00157)**]** **\[**[**Code**](https://people.eecs.berkeley.edu/~kewang/)**]** **\[**[**Project**](https://people.eecs.berkeley.edu/~kewang/sprih/)**]**
* [ ] LEMaRT: Label-Efficient Masked Region Transform for Image Harmonization(_CVPR '23_) **\[**[**Paper**](https://arxiv.org/abs/2304.13166)**]**
* [ ] Burstormer: Burst Image Restoration and Enhancement Transformer (_CVPR '23_) **\[**[**Paper**](https://arxiv.org/abs/2304.01194)**] \[**[**Code**](https://github.com/akshaydudhane16/Burstormer.git)**]**

### Video Forgery

* [ ] Explainable Manipulated Videos Detection Using Multimodal Large Language Models [![Static Badge](https://img.shields.io/badge/WWW_'25-dc3545)](https://dl.acm.org/doi/10.1145/3701716.3715283)
* [ ] Real-Time Video Forgery Detection via Vision-WiFi Silhouette Correspondence [![Static Badge](https://img.shields.io/badge/TMC_'25-dc3545)](https://ieeexplore.ieee.org/abstract/document/10726788)
* [ ] Dual-PST: Dual-Branch SpatioTemporal-Planar Network for Video Forgery Detection [![Static Badge](https://img.shields.io/badge/ICASSP_'25-ffc107)](https://ieeexplore.ieee.org/abstract/document/10890154)
* [ ] AvatarShield: Visual Reinforcement Learning for Human-Centric Video Forgery Detection [![Static Badge](https://img.shields.io/badge/arXiv_'25-6c757d)](https://arxiv.org/abs/2505.15173) [![GitHub](https://img.shields.io/github/stars/zhipeixu/AvatarShield?style=flat)](https://github.com/zhipeixu/AvatarShield)
* [ ] SEDN: A Spatiotemporal Encoder-Decoder Network for End-to-End Object Removal Forgery Detection in High-Resolution Videos [![Static Badge](https://img.shields.io/badge/TMM_'25-ffc107)](https://ieeexplore.ieee.org/document/10814702/)
* [ ] BusterX: MLLM-Powered AI-Generated Video Forgery Detection and Explanation [![Static Badge](https://img.shields.io/badge/arXiv_'25-6c757d)](https://arxiv.org/abs/2505.12620) [![GitHub](https://img.shields.io/github/stars/l8cv/BusterX?style=flat)](https://github.com/l8cv/BusterX)
* [ ] Face Forgery Video Detection via Temporal Forgery Cue Unraveling [![Static Badge](https://img.shields.io/badge/CVPR_'25-dc3545)](https://openaccess.thecvf.com/content/CVPR2025/html/Guo_Face_Forgery_Video_Detection_via_Temporal_Forgery_Cue_Unraveling_CVPR_2025_paper.html) [![GitHub](https://img.shields.io/github/stars/zhenglab/TFCU?style=flat)](https://github.com/zhenglab/TFCU)
* [ ] Generalizing Deepfake Video Detection with Plug-and-Play: Video-Level Blending and Spatiotemporal Adapter Tuning [![Static Badge](https://img.shields.io/badge/CVPR_'25-dc3545)](https://arxiv.org/abs/2408.17065) [![GitHub](https://img.shields.io/github/stars/YZY-stack/StA4Deepfake?style=flat)](https://github.com/YZY-stack/StA4Deepfake)

### Face Forgery

**人脸篡改**，篡改方法以及检测问题

* [ ] Mixture-of-Noises Enhanced Forgery-Aware Predictor for Multi-Face Manipulation Detection and Localization [![Static Badge](https://img.shields.io/badge/MM_'25-dc3545)](https://arxiv.org/abs/2408.02306)
* [ ] HAMLET-FFD: Hierarchical Adaptive Multi-modal Learning Embeddings Transformation for Face Forgery Detection [![Static Badge](https://img.shields.io/badge/MM_'25-dc3545)](https://arxiv.org/abs/2507.20913)
* [ ] Semantic Token Transformer for Face Forgery Detection [![Static Badge](https://img.shields.io/badge/TIFS_'25-dc3545)](https://ieeexplore.ieee.org/abstract/document/10988609)
* [ ] DeCLIP: Decoding CLIP Representations for Deepfake Localization [![Static Badge](https://img.shields.io/badge/WACV_'25-ffc107)](https://arxiv.org/abs/2409.08849)
* [ ] Stacking Brick by Brick: Aligned Feature Isolation for Incremental Face Forgery Detection [![Static Badge](https://img.shields.io/badge/CVPR_'25-dc3545)](https://arxiv.org/pdf/2411.11396) [![GitHub](https://img.shields.io/github/stars/beautyremain/SUR-LID?style=flat)](https://github.com/beautyremain/SUR-LID)
* [ ] Towards General Visual-Linguistic Face Forgery Detection [![Static Badge](https://img.shields.io/badge/CVPR_'25-dc3545)](https://arxiv.org/abs/2307.16545) [![GitHub](https://img.shields.io/github/stars/skjack/vlffd?style=flat)](https://github.com/skjack/vlffd)
* [ ] Forensics Adapter: Adapting CLIP for Generalizable Face Forgery Detection [![Static Badge](https://img.shields.io/badge/CVPR_'25-dc3545)](https://openaccess.thecvf.com/content/CVPR2025/html/Cui_Forensics_Adapter_Adapting_CLIP_for_Generalizable_Face_Forgery_Detection_CVPR_2025_paper.html) [![GitHub](https://img.shields.io/github/stars/OUC-VAS/ForensicsAdapter?style=flat)](https://github.com/OUC-VAS/ForensicsAdapter)
* [ ] FD-GAN: Generalizable and Robust Forgery Detection via Generative Adversarial Networks [![paper](https://img.shields.io/badge/IJCV_'24-dc3545)](https://link.springer.com/article/10.1007/s11263-024-02136-1)
* [ ] DiffusionFake: Enhancing Generalization in Deepfake Detection via Guided Stable Diffusion [![Static Badge](https://img.shields.io/badge/NeurIPS_'24-dc3545)](https://arxiv.org/pdf/2410.04372) [![GitHub](https://img.shields.io/github/stars/skJack/DiffusionFake?style=flat)](https://github.com/skJack/DiffusionFake)
* [ ] Can We Leave Deepfake Data Behind in Training Deepfake Detector? [![arXiv](https://img.shields.io/badge/arXiv_'24-6c757d)](http://arxiv.org/abs/2408.17052)
* [ ] Open-Set Deepfake Detection: A Parameter-Efficient Adaptation Method with Forgery Style Mixture [![arXiv](https://img.shields.io/badge/arXiv_'24-6c757d)](http://arxiv.org/abs/2408.12791)
* [ ] Hierarchical Forgery Classifier On Multi-modality Face Forgery Clues [![Static Badge](https://img.shields.io/badge/TMM_'24-ffc107)](https://arxiv.org/abs/2212.14629) [![GitHub](https://img.shields.io/github/stars/EdWhites/HFC-MFFD?style=flat)](https://github.com/EdWhites/HFC-MFFD)
* [ ] Identity-Driven Multimedia Forgery Detection via Reference Assistance [![paper](https://img.shields.io/badge/MM_'24-dc3545)](https://openreview.net/forum?id=aspe8HE0ZA)
* [ ] MCS-GAN: A Different Understanding for Generalization of Deep Forgery Detection (_TMM '23_) **\[**[**Paper**](https://ieeexplore.ieee.org/document/10141892)**]**
* [ ] Exposing the Deception: Uncovering More Forgery Clues for Deepfake Detection _(AAAI '24)_ **\[**[**Paper**](https://arxiv.org/abs/2403.01786)**]** **\[**[**Code**](https://github.com/QingyuLiu/Exposing-the-Deception)**]**
* [ ] Contrastive Learning for DeepFake Classification and Localization via Multi-Label Ranking _(CVPR '24)_
* [ ] Transcending Forgery Specificity with Latent Space Augmentation for Generalizable Deepfake Detection _(CVPR '24)_ **\[**[**Paper**](https://arxiv.org/abs/2311.11278)**]**
* [ ] Poisoned Forgery Face: Towards Backdoor Attacks on Face Forgery Detection _(ICLR '24)_ **\[**[**Paper**](https://openreview.net/pdf?id=8iTpB4RNvP)**]** **\[**[**Code**](https://github.com/JWLiang007/PFF)**]**
* [ ] Improving Fairness in Deepfake Detection _(WACV '24)_ **\[**[**Paper**](https://arxiv.org/abs/2306.16635)**]** **\[**[**Code**](https://github.com/littlejuyan/DF_Fairness)**]**
* [ ] Weakly-Supervised Deepfake Localization in Diffusion-Generated Images _(WACV '24)_ **\[**[**Paper**](https://arxiv.org/abs/2311.04584)**]** **\[**[**Code**](https://github.com/bit-ml/dolos)**]**
* [ ] Controllable Guide-Space for Generalizable Face Forgery Detection (_ICCV '23_) **\[**[**Paper**](https://arxiv.org/abs/2307.14039)**]**
* [ ] RAIRNet: Region-Aware Identity Rectification for Face Forgery Detection _(MM '23)_ **\[**[**Paper**](https://dl.acm.org/doi/10.1145/3581783.3612321)**]**
* [ ] Not All Steps are Created Equal: Selective Diffusion Distillation for Image Manipulation (_ICCV '23_) **\[**[**Paper**](https://arxiv.org/abs/2307.08448)**]** **\[**[**Code**](https://github.com/EnVision-Research/Selective-Diffusion-Distillation)**]**
* [ ] UCF: Uncovering Common Features for Generalizable Deepfake Detection _(ICCV '23)_ **\[**[**Paper**](https://arxiv.org/abs/2304.13949)**]**
* [ ] Learning Patch-Channel Correspondence for Interpretable Face Forgery Detection (_TIP '23_) **\[**[**Paper**](https://doi.org/10.1109/TIP.2023.3246793)**]** **\[**[**Code**](https://github.com/Jae35/IFFD)**]**
* [ ] Contrastive Multi-FaceForensics: An End-to-end Bi-grained Contrastive Learning Approach for Multi-face Forgery Detection _(arXiv '23')_ **\[**[**Paper**](https://arxiv.org/abs/2308.01520v1)**]**
* [ ] Two-in-one Knowledge Distillation for Efficient Facial Forgery Detection _(arXiv '23')_ **\[**[**Paper**](https://arxiv.org/abs/2302.10437)**]**
* [ ] AUNet: Learning Relations Between Action Units for Face Forgery Detection (_CVPR '23_) **\[**[**Paper**](http://openaccess.thecvf.com/content/CVPR2023/html/Bai_AUNet_Learning_Relations_Between_Action_Units_for_Face_Forgery_Detection_CVPR_2023_paper.html)**]**
* [ ] AltFreezing for More General Face Forgery Detection (_CVPR '23_) **\[**[**Paper**](http://openaccess.thecvf.com/content/CVPR2023/html/Wang_AltFreezing_for_More_General_Video_Face_Forgery_Detection_CVPR_2023_paper.html)**]** \*\*\[[Code](https://github.com/ZhendongWang6/AltFreezing)]88
* [ ] $F^2$Trans: High-Frequency Fine-Grained Transformer for Face Forgery Detection (_TIFS '23_) **\[**[**Paper**](https://ieeexplore.ieee.org/document/10004978)**]**
* [ ] On the Security of the One-and-a-Half-Class Classifier for SPAM Feature-Based Image Forensics (_TIFS '23_) **\[**[**Paper**](https://ieeexplore.ieee.org/document/10098583)**]**
* [ ] Multimodaltrace: Deepfake Detection Using Audiovisual Representation Learning (_CVPRW '23_) **\[**[**Paper**](https://openaccess.thecvf.com/content/CVPR2023W/WMF/html/Raza_Multimodaltrace_Deepfake_Detection_Using_Audiovisual_Representation_Learning_CVPRW_2023_paper.html)**]**
* [x] [MC-LCR: Multi-modal contrastive classification by locally correlated representations for effective face forgery detection](face-forgery/mc-lcr) (_KBS '22_) **\[**[**Paper**](https://arxiv.org/abs/2110.03290)**]**
* [x] [Multi-Scale Wavelet Transformer for Face Forgery Detection](face-forgery/multi-scale-wavelettransformer) (_ACCV '22_) **\[**[**Paper**](https://arxiv.org/abs/2210.03899)**]**
* [ ] Leveraging Real Talking Faces via Self-Supervision for Robust Forgery Detection (_CVPR '22_) **\[**[**Paper**](https://arxiv.org/abs/2201.07131)**]** **\[**[**Code**](https://github.com/ahaliassos/RealForensics)**]**
* [ ] SSTNet: Detecting Manipulated Faces Through Spatial, Steganalysis and Temporal Features (_ICASSP '20_) **\[**[**Paper**](https://ieeexplore.ieee.org/abstract/document/9053969/)**]**
* [x] Portrait shadow manipulation (_ACM MM / TOG '20_) **\[**[**Paper**](https://arxiv.org/abs/2005.08925)**]** **\[**[**Code**](https://github.com/google/portrait-shadow-manipulation)**]**

### Copy Move

**复制移动篡改定位**问题

* [ ] DSTNet: Distinguishing Source and Target Areas for Image Copy-Move Forgery Detection [![Static Badge](https://img.shields.io/badge/PR_'24-28a745)](https://link.springer.com/chapter/10.1007/978-3-031-78312-8_21)
* [ ] A Two-Phase Scheme by Integration of Deep and Corner Feature for Balanced Copy-Move Forgery Localization [![Static Badge](https://img.shields.io/badge/TII_'25-28a745)](https://ieeexplore.ieee.org/document/10738218/)
* [ ] DCM-Net: A Diffusion Model-Based Detection Network Integrating the Characteristics of Copy-Move Forgery [![Static Badge](https://img.shields.io/badge/TMM_'24-ffc107)](https://ieeexplore.ieee.org/document/10814718/)
* [ ] A Copy-move Forgery Detection Network based on Selective Sampling Attention and Low-cost Two-step Self-correlation Calculation [![Static Badge](https://img.shields.io/badge/TMM_'25-ffc107)](https://ieeexplore.ieee.org/abstract/document/10856558/)
* [ ] TransCMFD: An adaptive transformer for copy-move forgery detection [![Static Badge](https://img.shields.io/badge/Neurocomputing_'25-28a745)](https://doi.org/10.1016/j.neucom.2025.130110)
* [ ] Copy-move Forgery Image Detection based on Cross-Scale Modeling and Alternating Refinement [![Static Badge](https://img.shields.io/badge/TMM_'25-ffc107)](https://ieeexplore.ieee.org/abstract/document/10891504/)
* [ ] Copy-Move Detection in Optical Microscopy: A Segmentation Network and A Dataset [![Static Badge](https://img.shields.io/badge/arXiv_'24-6c757d)](https://arxiv.org/abs/2412.10258) [![GitHub](https://img.shields.io/github/stars/YoursEver/FakeParaEgg?style=flat)](https://github.com/YoursEver/FakeParaEgg)
* [ ] Copy-Move Forgery Detection and Question Answering for Remote Sensing Image [![Static Badge](https://img.shields.io/badge/arXiv_'24-6c757d)](https://arxiv.org/abs/2412.02575) [![GitHub](https://img.shields.io/github/stars/shenyedepisa/RSCMQA?style=flat)](https://github.com/shenyedepisa/RSCMQA)
* [ ] CMCF-Net: An End-to-End Context Multiscale Cross-Fusion Network for Robust Copy-Move Forgery Detection [![Static Badge](https://img.shields.io/badge/TMM_'24-ffc107)](https://doi.org/10.1109/TMM.2023.3345160)
* [ ] Robust Image Hashing via CP Decomposition and DCT for Copy Detection (_TOMM '24_) **\[**[**Paper**](https://dl.acm.org/doi/full/10.1145/3650112)**]**
* [ ] Lightweight and High-Precision Network for Image Copy-Move Forgery Detection (_SPL '24_) **\[**[**Paper**](https://doi.org/10.1109/LSP.2024.3400055)**]**
* [ ] Advancing Copy-Move Manipulation Detection in Complex Image Scenarios Through Multiscale Detector (_IEEE Access ‘24_) **\[**[**Paper**](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10521517)**]**
* [ ] Cascaded Adaptive Graph Representation Learning for Image Copy-Move Forgery Detection (_TOMM '24_) **\[**[**Paper**](https://dl.acm.org/doi/abs/10.1145/3669905)**]**
* [ ] Image Copy-Move Forgery Detection and Localization Scheme: How to Avoid Missed Detection and False Alarm _(arXiv '24)_ **\[**[**Paper**](https://arxiv.org/abs/2406.03271v1)**]** **\[**[**Code**](https://github.com/LUZW1998/CMFDL)**]**
* [ ] Image Copy-Move Forgery Detection via Deep PatchMatch and Pairwise Ranking Learning [![paper](https://img.shields.io/badge/TIP_'25-dc3545)](https://arxiv.org/abs/2404.17310) _(_~~_arXiv '24_~~_)_ **\[**[**Paper**](https://arxiv.org/abs/2404.17310)**]**
* [ ] Object-level Copy-Move Forgery Image Detection based on Inconsistency Mining (_WWW '24_) **\[**[**Paper**](https://arxiv.org/abs/2404.00611)**]**
* [ ] UCM-Net: A U-Net-Like Tampered-Region-Related Framework for Copy-Move Forgery Detection (_TMM '24_) **\[**[**Paper**](https://ieeexplore.ieee.org/document/10109179)**]**
* [ ] An effective image copy-move forgery detection using entropy image _(arXiv '23)_ **\[**[**Paper**](https://arxiv.org/abs/2312.11793)**]**
* [ ] CMFDFormer: Transformer-based Copy-Move Forgery Detection with Continual Learning _(arXiv '23)_ **\[**[**Paper**](https://arxiv.org/abs/2311.13263)**]**
* [ ] An approach for copy-move image multiple forgery detection based on an optimized pre-trained deep learning model _(KBS '23)_ **\[**[**Paper**](https://www.sciencedirect.com/science/article/pii/S0950705123002587)**]**
* [ ] Image Copy-Move Forgery Detection via Deep Cross-Scale PatchMatch (_ICME '23_) **\[**[**Paper**](https://arxiv.org/abs/2308.04188)**]**
* [x] [BusterNet: Detecting Copy-Move Image Forgery with Source/Target Localization](copy-move/busternet) (_ECCV '18_) **\[**[**Paper**](http://openaccess.thecvf.com/content_ECCV_2018/html/Rex_Yue_Wu_BusterNet_Detecting_Copy-Move_ECCV_2018_paper.html)**]** **\[**[**Code**](https://github.com/isi-vista/BusterNet)**]**
* [x] [A Serial Image Copy-Move Forgery Localization Scheme With Source/Target Distinguishment](copy-move/cmsdnet) (_TMM '20_) **\[**[**Paper**](https://ieeexplore.ieee.org/abstract/document/9207851/)**]** **\[**[**Code**](https://github.com/imagecbj/A-serial-image-copy-move-forgery-localization-scheme-with-source-target-distinguishment)**]**
* [x] [DOA-GAN: Dual-Order Attentive Generative Adversarial Network for Image Copy-Move Forgery Detection and Localization](copy-move/doa-gan) (_CVPR '20_) **\[**[**Paper**](http://openaccess.thecvf.com/content_CVPR_2020/html/Islam_DOA-GAN_Dual-Order_Attentive_Generative_Adversarial_Network_for_Image_Copy-Move_Forgery_CVPR_2020_paper.html)**]** **\[**[**Code**](https://github.com/asrafulashiq/doagan_clean)**]**
* [x] [Two-Stage Copy-Move Forgery Detection with Self Deep Matching and Proposal SuperGlue](copy-move/selfdm-ps) (_TIP '22_) **\[**[**Paper**](https://arxiv.org/abs/2012.08697)**]**
* [ ] QDL-CMFD: A Quality-independent and deep Learning-based Copy-Move image forgery detection method (_Neurocomputing '22_) **\[**[**Paper**](https://www.sciencedirect.com/science/article/pii/S0925231222011031)**]** **\[**[**Code**](https://github.com/MehradAria/QDL-CMFD)**]**
* [ ] [Shrinking the Semantic Gap: Spatial Pooling of Local Moment Invariants for Copy-Move Forgery Detection](copy-move/word2phrasecmfd) _(TIFS '23)_ **\[**[**Paper**](https://arxiv.org/abs/2207.09135)**]** **\[**[**Code**](https://github.com/ChaoWang1016/word2phraseCMFD)**]**

### Image Inpainting

* [ ] Dense Feature Interaction Network for Image Inpainting Localization [![paper](https://img.shields.io/badge/TIFS_'25-dc3545)](https://arxiv.org/abs/2408.02191) [![GitHub](https://img.shields.io/github/stars/Boombb/DeFI-Net_Inpainting?style=flat)](https://github.com/Boombb/DeFI-Net_Inpainting)
* [ ] Image Inpainting Detection via Dual Guidance of Uncertainty and Precise Boundary Information [![Static Badge](https://img.shields.io/badge/TCSVT_'25-ffc107)](https://ieeexplore.ieee.org/abstract/document/11005519)
* [ ] COCO-Inpaint: A Benchmark for Image Inpainting Detection and Manipulation Localization [![Static Badge](https://img.shields.io/badge/arXiv_'25-6c757d)](https://arxiv.org/abs/2504.18361)
* [ ] A Large-scale AI-generated Image Inpainting Benchmark [![Static Badge](https://img.shields.io/badge/arXiv_'25-6c757d)](https://arxiv.org/abs/2502.06593) [![GitHub](https://img.shields.io/github/stars/mever-team/DiQuID?style=flat)](https://github.com/mever-team/DiQuID)
* [ ] InpDiffusion: Image Inpainting Localization via Conditional Diffusion Models [![Static Badge](https://img.shields.io/badge/arXiv_'25-6c757d)](https://arxiv.org/abs/2501.02816) [![GitHub](https://img.shields.io/github/stars/QixianHao/Inpaint32K_dataset?style=flat)](https://github.com/QixianHao/Inpaint32K_dataset)
* [ ] Wavelet based inpainting detection [![paper](https://img.shields.io/badge/arXiv_'24-6c757d)](http://arxiv.org/abs/2408.06429)
* [ ] Enhanced Wavelet Scattering Network for image inpainting detection [![paper](https://img.shields.io/badge/arXiv_'24-6c757d)](http://arxiv.org/abs/2409.17023) [![GitHub](https://img.shields.io/github/stars/jmaba/Wavelet-based-inpainting-detection?style=flat)](https://github.com/jmaba/Wavelet-based-inpainting-detection)

### Tamper Text in Detection

图像中的**文本篡改检测**问题 (parts of)

* [ ] RealDTT: Towards a Comprehensive Real-World Dataset for Tampered Text Detection [![paper](https://img.shields.io/badge/IJCV_'25-dc3545)](https://link.springer.com/article/10.1007/s11263-025-02515-2) [![GitHub](https://img.shields.io/github/stars/edmundhaohao/RealDTT?style=flat)](https://github.com/edmundhaohao/RealDTT)
* [ ] Revisiting Tampered Scene Text Detection in the Era of Generative AI [![paper](https://img.shields.io/badge/ICCV_'25-dc3545)](https://arxiv.org/abs/2407.21422) [![GitHub](https://img.shields.io/github/stars/qcf-568/OSTF?style=flat)](https://github.com/qcf-568/OSTF)
* [ ] ADCD-Net: Robust Document Image Forgery Localization via Adaptive DCT Feature and Hierarchical Content Disentanglement [![paper](https://img.shields.io/badge/ICCV_'25-dc3545)](https://arxiv.org/abs/2507.16397) [![GitHub](https://img.shields.io/github/stars/KAHIMWONG/ADCD-Net?style=flat)](https://github.com/KAHIMWONG/ADCD-Net)
* [ ] FantasyID: A dataset for detecting digital manipulations of ID-documents [![Static Badge](https://img.shields.io/badge/IJCB_'25-28a745)](https://arxiv.org/abs/2507.20808) [Dataset](https://www.idiap.ch/paper/fantasyid)
* [ ] Towards Generalized Physical Occlusion Detection On Documents [![paper](https://img.shields.io/badge/MM_'25-dc3545)](readme)
* [ ] DITL²: Dual-Stage Invariance Transfer Learning for Generalizable Document Image Tampering Localization [![paper](https://img.shields.io/badge/MM_'25-dc3545)](readme)
* [ ] Document image forgery detection and localization in desensitization scenarios [![Static Badge](https://img.shields.io/badge/SIGPRO_'25-28a745)](https://www.sciencedirect.com/science/article/pii/S0165168425002373)
* [ ] Handwritten Signature Verification via Multimodal Consistency Learning [![paper](https://img.shields.io/badge/TIFS_'25-dc3545)](https://ieeexplore.ieee.org/document/10950350/)
* [ ] Cross-Attention Based Two-Branch Networks for Document Image Forgery Localization in the Metaverse [![Static Badge](https://img.shields.io/badge/TOMM_'25-ffc107)](https://doi.org/10.1145/3686158)
* [ ] Explainable Tampered Text Detection via Multimodal Large Models [![paper](https://img.shields.io/badge/arXiv_'24-6c757d)](http://arxiv.org/abs/2412.14816)
* [ ] Enhancing Tampered Text Detection through Frequency Feature Fusion and Decomposition [![conf](https://img.shields.io/badge/ECCV_'24-ffc107)](https://www.ecva.net/papers/eccv_2024/papers_ECCV/papers/04834.pdf)
* [ ] Delving into Adversarial Robustness on Document Tampering Localization [![conf](https://img.shields.io/badge/ECCV_'24-ffc107)](https://www.ecva.net/papers/eccv_2024/papers_ECCV/papers/08224.pdf)
* [ ] Image-based Freeform Handwriting Authentication with Energy-oriented Self-Supervised Learning [![paper](https://img.shields.io/badge/TMM_'24-ffc107)](https://arxiv.org/abs/2408.09676)
* [ ] Generalized Tampered Scene Text Detection in the era of Generative AI [![paper](https://img.shields.io/badge/arXiv_'24-6c757d)](https://arxiv.org/abs/2407.21422)
* [ ] A Two-Stage Dual-Path Framework for Text Tampering Detection and Recognition _(arXiv '24)_ **\[**[**Paper**](https://arxiv.org/abs/2402.13545)**]**
* [ ] CTP-Net: Character Texture Perception Network for Document Image Forgery Localization (_arXiv '23_) **\[**[**Paper**](https://arxiv.org/abs/2308.02158v1)**]** [![GitHub](https://img.shields.io/github/stars/FCTMdataset/FCTM?style=flat)](https://github.com/FCTMdataset/FCTM)
* [ ] Toward Real Text Manipulation Detection: New Dataset and New Solution _(arXiv '23)_ **\[**[**Paper**](https://arxiv.org/abs/2312.06934)**]** **\[**[**Code**](https://github.com/DrLuo/RTM)**]** [![paper](https://img.shields.io/badge/PR_'25-ffc107)](https://ieeexplore.ieee.org/abstract/document/10883001/) _❗Updated_
* [ ] Towards Robust Tampered Text Detection in Document Image: New dataset and New Solution (_CVPR '23_) **\[**[**Paper**](https://openaccess.thecvf.com/content/CVPR2023/papers/Qu_Towards_Robust_Tampered_Text_Detection_in_Document_Image_New_Dataset_CVPR_2023_paper.pdf)**]** **\[**[**Code**](https://github.com/qcf-568/DocTamper)**]**
* [ ] Progressive Supervision for Tampering Localization in Document Images (_ICONIP '23_) **\[**[**Paper**](https://link.springer.com/chapter/10.1007/978-981-99-8184-7_11)**]**
* [ ] SigScatNet: A Siamese + Scattering based Deep Learning Approach for Signature Forgery Detection and Similarity Assessment _(arXiv '23)_ **\[**[**Paper**](https://arxiv.org/pdf/2311.05579.pdf)**]**
* [ ] Image Generation and Learning Strategy for Deep Document Forgery Detection _(arXiv '23)_ **\[**[**Paper**](https://arxiv.org/abs/2311.03650)**]**
* [ ] Forgery-free signature verification with stroke-aware cycle-consistent generative adversarial network _(Neurocomputing '22)_ **\[**[**Paper**](https://doi.org/10.1016/j.neucom.2022.08.017)**]** **\[**[**Code**](https://github.com/KAKAFEI123/Stroke-cCycleGAN)**]**
* [ ] Document Forgery Detection in the Context of Double JPEG Compression _(ICPR '22)_ **\[**[**Paper**](https://link.springer.com/chapter/10.1007/978-3-031-37745-7_5)**]**

### Low Level Vision

Related resources:

* [https://github.com/Kobaayyy/Awesome-ICCV2021-Low-Level-Vision](https://github.com/Kobaayyy/Awesome-ICCV2021-Low-Level-Vision)
* [https://github.com/lcybuzz/Low-Level-Vision-Paper-Record](https://github.com/lcybuzz/Low-Level-Vision-Paper-Record)

Low-level tasks include super-resolution, denoise, dehze, low-light enhancement, etc. High-level tasks include classification, detection, segmentation, etc. segmentation, and so on. However, the ones I have listed here are probably still mainly related to tampering detection.

> Testing the new layout of paper title.
>
> 📖Paper, 👨‍💻Code, 📦Dataset, 🔗Other links, 📜News,
>
> \*Equal contribution. #Corresponding author.

* [ ] Q-Instruct: Improving Low-level Visual Abilities for Multi-modality Foundation Models [![arXiv](https://img.shields.io/badge/CVPR_'24-dc3545)](https://openaccess.thecvf.com/content/CVPR2024/html/Wu_Q-Instruct_Improving_Low-level_Visual_Abilities_for_Multi-modality_Foundation_Models_CVPR_2024_paper.html) [![GitHub](https://img.shields.io/github/stars/qcf-568/MIML?style=flat)](https://github.com/Q-Future/Q-Instruct/)
*   [ ] (**EVP**) Explicit Visual Prompting for Low-Level Structure Segmentations (_CVPR '23_) [📖](https://arxiv.org/abs/2303.10883), [👨‍💻](https://github.com/NiFangBaAGe/Explicit-Visual-Prompt) (_including defocus blur, shadow, forgery, camouflaged dection_)

    > [Weihuang Liu](https://github.com/nifangbaage)<sup>1</sup>, [Xi Shen](https://xishen0220.github.io/)<sup>2</sup>, [Chi-Man Pun](https://www.cis.um.edu.mo/~cmpun/)<sup>#,1</sup>, [Xiaodong Cun](https://vinthony.github.io/)<sup>#,2</sup>
    >
    > <sup>1</sup>University of Macau <sup>2</sup>Tencent AI Lab
*   [ ] SYENet: A Simple Yet Effective Network for Multiple Low-Level Vision Tasks with Real-time Performance on Mobile Device (_ICCV '23_) [📖](https://arxiv.org/abs/2308.08137), [👨‍💻](https://github.com/sanechips-multimedia/syenet)

    > [Weiran Gou](https://github.com/WeiranGou)<sup>∗1,2</sup>, Ziyao Yi<sup>∗1,2</sup>, Yan Xiang<sup>1,2</sup>, Shaoqing Li<sup>1,2</sup>, Zibin Liu<sup>1,2</sup>, Dehui Kong<sup>1,2</sup>, Ke Xu<sup>#1,2</sup>
    >
    > <sup>1</sup>State Key Laboratory of Mobile Network and Mobile Multimedia Technology, <sup>2</sup>Sanechips Technology, Chengdu, China
*   [ ] Q-Bench: A Benchmark for General-Purpose Foundation Models on Low-level Vision (_ICLR_ '24\_) [📖](https://arxiv.org/abs/2309.14181), [👨‍💻](https://github.com/VQAssessment/Q-Bench)

    > [Haoning Wu](https://teowu.github.io/)<sup>1\*</sup>, [Zicheng Zhang](https://github.com/zzc-1998)<sup>2\*</sup>, [Erli Zhang](https://github.com/ZhangErliCarl/)<sup>1\*</sup>, [Chaofeng Chen](https://chaofengc.github.io/)<sup>1</sup>, [Liang Liao](https://liaoliang92.github.io/)<sup>1</sup>, [Annan Wang](https://github.com/AnnanWangDaniel)<sup>1</sup>, [Chunyi Li](https://github.com/lcysyzxdxc)<sup>2</sup>, [Wenxiu Sun](https://wenxiusun.com/)<sup>3</sup>, [Qiong Yan](https://scholar.google.com/citations?user=uT9CtPYAAAAJ\&hl=en)<sup>3</sup>, [Guangtao Zhai](https://ee.sjtu.edu.cn/en/FacultyDetail.aspx?id=24\&infoid=153\&flag=153)<sup>2</sup>, [Weisi Lin](https://personal.ntu.edu.sg/wslin/Home.html)<sup>1#</sup>
    >
    > <sup>1</sup>Nanyang Technological University, <sup>2</sup>Shanghai Jiaotong University, <sup>3</sup>Sensetime Research

### Image Matching

**特征匹配**，图像匹配问题。

* [ ] FMRT: Learning Accurate Feature Matching with Reconciliatory Transformer(_arXiv '23_) **\[**[**Paper**](https://arxiv.org/abs/2310.13605)**]**
* [x] [LoFTR: Detector-Free Local Matching with Transformers](image-matching/loftr) (_CVPR '21_) **\[**[**Paper**](https://arxiv.org/abs/2104.00680)**]** **\[**[**Code**](https://github.com/zju3dv/LoFTR)**]**
* [ ] PATS: Patch Area Transportation with Subdivision for Local Feature Matching (_CVPR '23_) **\[**[**Paper**](https://arxiv.org/abs/2303.07700)**]** **\[**[**Code**](https://github.com/zju3dv/pats)**]** **\[**[**Project**](https://zju3dv.github.io/pats/)**]**
* [ ] Adaptive Spot-Guided Transformer for Consistent Local Feature Matching (_CVPR '23_) **\[**[**Paper**](https://arxiv.org/abs/2303.16624)**]** **\[**[**Code**](https://github.com/ASTR2023/ASTR)**]** **\[**[**Project**](https://astr2023.github.io/)**]**
* [ ] ObjectMatch: Robust Registration using Canonical Object Correspondences (_CVPR '23_) **\[**[**Paper**](https://arxiv.org/abs/2212.01985)**]** **\[**[**Code**](https://github.com/cangumeli/ObjectMatch)**]** **\[**[**Project**](https://cangumeli.github.io/ObjectMatch/)**]**

### Object Detection

**目标检测**，包括伪装物体目标检测和突出目标检测，COD以及SOD。

* [ ] HEAP: Unsupervised Object Discovery and Localization with Contrastive Grouping _(AAAI '24)_ **\[**[**Paper**](https://arxiv.org/abs/2312.17492)**]**
* [ ] Endow SAM with Keen Eyes: Temporal-spatial Prompt Learning for Video Camouflaged Object Detection _(CVPR '24)_
* [ ] VSCode: General Visual Salient and Camouflaged Object Detection with 2D Prompt Learning _(CVPR '24)_ **\[**[**Paper**](https://arxiv.org/abs/2311.15011)**]**
* [ ] Weakly Supervised Open-Vocabulary Object Detection _(AAAI '24)_ **\[**[**Paper**](https://arxiv.org/abs/2312.12437)**]**
* [ ] OTA: Optimal Transport Assignment for Object Detection (_CVPR '21_) **\[**[**Paper**](https://arxiv.org/abs/2103.14259)**]** **\[**[**Code**](https://github.com/Megvii-BaseDetection/OTA)**]**
* [ ] Consistency-basd Active Learning for Object Detection (_CVPRW '22_) **\[**[**Paper**](http://128.84.21.203/abs/2103.10374)**]** **\[**[**Code**](https://github.com/we1pingyu/CALD)**]**
* [ ] [Zoom In and Out: A Mixed-scale Triplet Network for Camouflaged Object Detection](object-dection/zoomnet-cod) (_CVPR '22_) **\[**[**Paper**](https://arxiv.org/abs/2203.02688)**]** **\[**[**Code**](https://github.com/lartpang/ZoomNet)**]**
* [ ] Unsupervised Object Localization: Observing the Background to Discover Objects (_CVPR '23_) **\[**[**Paper**](https://arxiv.org/abs/2212.07834)**]** **\[**[**Code**](https://github.com/valeoai/FOUND)**]**
* [ ] Camouflaged Object Detection with Feature Decomposition and Edge Reconstruction (_CVPR '23_) **\[**[**Paper**](https://openreview.net/pdf?id=lin5jPqCQ6)**]** **\[**[**Code**](https://github.com/ChunmingHe/FEDER)**]**
* [ ] Feature Shrinkage Pyramid for Camouflaged Object Detection with Transformers (_CVPR '23_) **\[**[**Paper**](https://arxiv.org/abs/2303.14816)**]** **\[**[**Code**](https://github.com/ZhouHuang23/FSPNet)**]**
* [ ] Locate, Refine and Restore: A Progressive Enhancement Network for Camouflaged Object Detection (_IJCAI '23_) **\[**[**Paper**](https://www.ijcai.org/proceedings/2023/0124.pdf)**]**
* [ ] Spatial-Aware Token for Weakly Supervised Object Localization (_ICCV '23_) **\[**[**Paper**](https://arxiv.org/abs/2303.10438)**]** **\[**[**Code**](https://github.com/wpy1999/SAT)**]**
* [ ] Generative Prompt Model for Weakly Supervised Object Localization (_ICCV '23_) **\[**[**Paper**](https://arxiv.org/abs/2307.09756)**]** **\[**[**Code**](https://github.com/callsys/GenPromp)**]**
* [ ] Category-aware Allocation Transformer for Weakly Supervised Object Localization (_ICCV '23_) **\[**[**Paper**](https://openaccess.thecvf.com/content/ICCV2023/html/Chen_Category-aware_Allocation_Transformer_for_Weakly_Supervised_Object_Localization_ICCV_2023_paper.html)**]**

### Semantic Segmentation

语义分割，将图片中完整语义（具有标签或者类别）的部分分割出来。不仅要进行目标检测检测到图像中的物体，还需要对每个像素分类。

* [ ] [Generative Semantic Segmentation](semantic-segmentation/gss) (_CVPR '23_) **\[**[**Paper**](https://arxiv.org/abs/2303.11316)**]** **\[**[**Code**](https://github.com/fudan-zvg/GSS)**]**
* [ ] EfficientViT: Lightweight Multi-Scale Attention for On-Device Semantic Segmentation **\[**[**Paper**](https://arxiv.org/abs/2205.14756)**]** **\[**[**Code**](https://github.com/mit-han-lab/efficientvit)**]**
* [ ] CAT-Seg: Cost Aggregation for Open-Vocabulary Semantic Segmentation **\[**[**Paper**](https://arxiv.org/abs/2303.11797)**]** **\[**[**Code**](https://github.com/KU-CVLAB/CAT-Seg)**]** **\[**[**Project**](https://ku-cvlab.github.io/CAT-Seg/)**]** **\[**[**Note\_community**](https://blog.csdn.net/P_LarT/article/details/131083586)\*\*]

### Anomaly Detection

异常检测，通常用于发现与正常模式或预期模式不符的图像与视频。

* [ ] Contextual Affinity Distillation for Image Anomaly Detection _(WACV '24)_ **\[**[**Paper**](https://arxiv.org/abs/2307.03101)**]**
* [ ] PromptAD: Zero-Shot Anomaly Detection Using Text Prompts _(WACV '24)_ **\[**[**Paper**](https://openaccess.thecvf.com/content/WACV2024/html/Li_PromptAD_Zero-Shot_Anomaly_Detection_Using_Text_Prompts_WACV_2024_paper.html)**]**
* [ ] Holistic Representation Learning for Multitask Trajectory Anomaly Detection _(WACV '24)_ **\[**[**Paper**](https://arxiv.org/abs/2311.01851)**]** **\[**[**Code**](https://alexandrosstergiou.github.io/project_pages/TrajREC/index.html)**]**

### Image Steganography

* [ ] Finding Incompatible Blocks for Reliable JPEG Steganalysis [![paper](https://img.shields.io/badge/TIFS_'24-dc3545)](https://arxiv.org/abs/2402.13660)
* [ ] LiDiNet: A Lightweight Deep Invertible Network for Image-in-Image Steganography [![paper](https://img.shields.io/badge/TIFS_'24-dc3545)](https://doi.org/10.1109/TIFS.2024.3463547)

### Useful Links

1. CVPR 2025 Accepted Papers [https://cvpr.thecvf.com/Conferences/2025/AcceptedPapers/](https://cvpr.thecvf.com/Conferences/2025/AcceptedPapers/)
2. ECCV 2024 Accepted papers [https://eccv.ecva.net/virtual/2024/papers.html?filter=titles/](https://eccv.ecva.net/virtual/2024/papers.html?filter=titles/)
3. IJCAI 2024 Main Track Accepted Papers [https://ijcai24.org/main-track-accepted-papers/](https://ijcai24.org/main-track-accepted-papers/)
4. ICLR 2024 Papers List [https://openreview.net/group?id=ICLR.cc/2024/Conference](https://openreview.net/group?id=ICLR.cc/2024/Conference)
5. WACV 2024 Papers [https://openaccess.thecvf.com/WACV2024](https://openaccess.thecvf.com/WACV2024)
6. MM 2023 Proceedings [https://dl.acm.org/doi/proceedings/10.1145/3581783](https://dl.acm.org/doi/proceedings/10.1145/3581783)
7. ICML 2023 https://dblp.org/db/conf/icml/icml2023.html
8. ICCV 2023 Paper List [https://huggingface.co/spaces/ICCV2023/ICCV2023-papers](https://huggingface.co/spaces/ICCV2023/ICCV2023-papers)
9. AAAI 2023 [https://dblp.org/db/conf/aaai/aaai2023.html](https://dblp.org/db/conf/aaai/aaai2023.html)
10. SIGGRAPH _unofficial_ [https://kesen.realtimerendering.com/](https://kesen.realtimerendering.com/) eg SIGGRAPH 2023 [https://kesen.realtimerendering.com/sig2023.html](https://kesen.realtimerendering.com/sig2023.html)
11. TIFS [https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=10206](https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=10206)
12. [More...](related/papersource)

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