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The rapid progression of generative AI (GenAI) technologies has heightened concerns regarding the misuse of AI-generated imagery. To address this issue, robust detection methods have emerged as particularly compelling, especially in…

Graphics · Computer Science 2025-04-07 Hongfei Cai , Chi Liu , Sheng Shen , Youyang Qu , Peng Gui

Synthetic image generation has opened up new opportunities but has also created threats in regard to privacy, authenticity, and security. Detecting fake images is of paramount importance to prevent illegal activities, and previous research…

Computer Vision and Pattern Recognition · Computer Science 2023-02-27 Md Awsafur Rahman , Bishmoy Paul , Najibul Haque Sarker , Zaber Ibn Abdul Hakim , Shaikh Anowarul Fattah

The growing reliance on AI-identified digital evidence raises significant concerns about its reliability, particularly as large language models (LLMs) are increasingly integrated into forensic investigations. This paper proposes a…

Cryptography and Security · Computer Science 2026-02-25 Jeel Piyushkumar Khatiwala , Daniel Kwaku Ntiamoah Addai , Weifeng Xu

The proliferation of AI-generated media poses significant challenges to information authenticity and social trust, making reliable detection methods highly demanded. Methods for detecting AI-generated media have evolved rapidly, paralleling…

Computer Vision and Pattern Recognition · Computer Science 2025-02-13 Yueying Zou , Peipei Li , Zekun Li , Huaibo Huang , Xing Cui , Xuannan Liu , Chenghanyu Zhang , Ran He

Deepfakes, synthetic media created using advanced AI techniques, pose a growing threat to information integrity, particularly in politically sensitive contexts. This challenge is amplified by the increasing realism of modern generative…

Computer Vision and Pattern Recognition · Computer Science 2025-10-08 Victor Livernoche , Akshatha Arodi , Andreea Musulan , Zachary Yang , Adam Salvail , Gaétan Marceau Caron , Jean-François Godbout , Reihaneh Rabbany

Recently, generated images could reach very high quality, even human eyes could not tell them apart from real images. Although there are already some methods for detecting generated images in current forensic community, most of these…

Computer Vision and Pattern Recognition · Computer Science 2019-12-25 Xinsheng Xuan , Bo Peng , Wei Wang , Jing Dong

Recent generative models demonstrate impressive performance on synthesizing photographic images, which makes humans hardly to distinguish them from pristine ones, especially on realistic-looking synthetic facial images. Previous works…

Computer Vision and Pattern Recognition · Computer Science 2025-01-15 Hao Wang , Cheng Deng , Zhidong Zhao

Over the past years, image generation and manipulation have achieved remarkable progress due to the rapid development of generative AI based on deep learning. Recent studies have devoted significant efforts to address the problem of face…

Computer Vision and Pattern Recognition · Computer Science 2024-02-15 Yuhang Lu , Touradj Ebrahimi

Recent advances in diffusion models have enabled the creation of deceptively real images, posing significant security risks when misused. In this study, we empirically show that different timesteps of DDIM inversion reveal varying subtle…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Yixin Wu , Feiran Zhang , Tianyuan Shi , Ruicheng Yin , Zhenghua Wang , Zhenliang Gan , Xiaohua Wang , Changze Lv , Xiaoqing Zheng , Xuanjing Huang

Recent advances in generative AI have significantly enhanced the realism of multimodal media manipulation, thereby posing substantial challenges to manipulation detection. Existing manipulation detection and grounding approaches…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Yuchen Zhang , Yaxiong Wang , Kecheng Han , Yujiao Wu , Lianwei Wu , Li Zhu , Zhedong Zheng

The proliferation of deepfake technologies poses urgent challenges and serious risks to digital integrity, particularly within critical sectors such as forensics, journalism, and the legal system. While existing detection systems have made…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Shahroz Tariq , Simon S. Woo , Priyanka Singh , Irena Irmalasari , Saakshi Gupta , Dev Gupta

As generative models continue to evolve, detecting AI-generated images remains a critical challenge. While effective detection methods exist, they often lack formal interpretability and may rely on implicit assumptions about fake content,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Haim Zisman , Uri Shaham

As latent diffusion models (LDMs) democratize image generation capabilities, there is a growing need to detect fake images. A good detector should focus on the generative models fingerprints while ignoring image properties such as semantic…

Computer Vision and Pattern Recognition · Computer Science 2025-02-27 Anirudh Sundara Rajan , Utkarsh Ojha , Jedidiah Schloesser , Yong Jae Lee

Recent generative models produce images with a level of authenticity that makes them nearly indistinguishable from real photos and artwork. Potential harmful use cases of these models, necessitate the creation of robust synthetic image…

Computer Vision and Pattern Recognition · Computer Science 2025-01-15 Delyan Boychev , Radostin Cholakov

Multimodal deepfakes involving audiovisual manipulations are a growing threat because they are difficult to detect with the naked eye or using unimodal deep learningbased forgery detection methods. Audiovisual forensic models, while more…

Computer Vision and Pattern Recognition · Computer Science 2024-11-15 Sahibzada Adil Shahzad , Ammarah Hashmi , Yan-Tsung Peng , Yu Tsao , Hsin-Min Wang

As generative video models become increasingly realistic, detecting AI-generated videos requires systems that offer both accuracy and interpretability. However, applying Multimodal Large Language Models (MLLMs) to video forensics is…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Haiquan Wen , Yiwei He , Zhenglin Huang , Tianxiao Li , Zihan Yu , Xingru Huang , Lu Qi , Baoyuan Wu , Xiangtai Li , Guangliang Cheng

The rapid advancement in generative AI models has enabled the creation of photorealistic images. At the same time, there are growing concerns about the potential misuse and dangers of generated content, as well as a pressing need for…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Zhenhan Huang , Pin-Yu Chen , Tejaswini Pedapati , Jianxi Gao

The threats posed by AI-generated media, particularly deepfakes, are now raising significant challenges for multimedia forensics, misinformation detection, and biometric system resulting in erosion of public trust in the legal system,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-05 Nusrat Tasnim , Kutub Uddin , Khalid Mahmood Malik

The recent wave of AI research has enabled a new brand of synthetic media, called deepfakes. Deepfakes have impressive photorealism, which has generated exciting new use cases but also raised serious threats to our increasingly digital…

Computer Vision and Pattern Recognition · Computer Science 2023-04-18 Nikolaos Giatsoglou , Symeon Papadopoulos , Ioannis Kompatsiaris

Artificial Intelligence (AI) has made it possible for anyone to create images, audio, and video with unprecedented ease, enriching education, communication, and creative expression. At the same time, the rapid rise of AI-generated media has…

Multimedia · Computer Science 2025-11-18 Shail Desai , Aditya Pawar , Li Lin , Xin Wang , Shu Hu