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Related papers: Detecting AI-Generated Video via Frame Consistency

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The remarkable visual fidelity of recent commercial video generative models, such as Sora and Veo, renders robust AI-generated video detection increasingly essential to prevent synthetic content from being indistinguishable from real videos…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Zixi Wei , Huixuaun Zhang , Xiaojun Wan

Following the recent initiatives for the democratization of AI, deep fake generators have become increasingly popular and accessible, causing dystopian scenarios towards social erosion of trust. A particular domain, such as biological…

Computer Vision and Pattern Recognition · Computer Science 2021-05-21 Ilke Demir , Umur A. Ciftci

The flourishing of video generation technologies has endangered the credibility of real-world information and intensified the demand for AI-generated video detectors. Despite some progress, the lack of high-quality real-world datasets…

Computer Vision and Pattern Recognition · Computer Science 2025-06-13 Weiliang Chen , Wenzhao Zheng , Yu Zheng , Lei Chen , Jie Zhou , Jiwen Lu , Yueqi Duan

With the rapid proliferation of image generative models, the authenticity of digital images has become a significant concern. While existing studies have proposed various methods for detecting AI-generated content, current benchmarks are…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Huixuan Zhang , Xiaojun Wan

The rapid advancement of video generation models has made it increasingly challenging to distinguish AI-generated videos from real ones. This issue underscores the urgent need for effective AI-generated video detectors to prevent the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Zhenliang Ni , Qiangyu Yan , Mouxiao Huang , Tianning Yuan , Yehui Tang , Hailin Hu , Xinghao Chen , Yunhe Wang

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 misuse of AI-driven video generation technologies has raised serious social concerns, highlighting the urgent need for reliable AI-generated video detectors. However, most existing methods are limited to binary classification and lack…

Computer Vision and Pattern Recognition · Computer Science 2026-05-18 Yifei Li , Wenzhao Zheng , Yanran Zhang , Runze Sun , Yu Zheng , Lei Chen , Jie Zhou , Jiwen Lu

Advances in AI-generated content have led to wide adoption of large language models, diffusion-based visual generators, and synthetic audio tools. However, these developments raise critical concerns about misinformation, copyright…

Computation and Language · Computer Science 2025-09-30 Lele Cao

High-quality video generation is crucial for many fields, including the film industry and autonomous driving. However, generating videos with spatiotemporal consistencies remains challenging. Current methods typically utilize attention…

Computer Vision and Pattern Recognition · Computer Science 2025-04-28 Haotian Dong , Xin Wang , Di Lin , Yipeng Wu , Qin Chen , Ruonan Liu , Kairui Yang , Ping Li , Qing Guo

Generative models have enabled the creation of highly realistic facial-synthetic images, raising significant concerns due to their potential for misuse. Despite rapid advancements in the field of deepfake detection, developing efficient…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Yue-Hua Han , Tai-Ming Huang , Kai-Lung Hua , Jun-Cheng Chen

The exponential progress in generative AI poses serious implications for the credibility of all real images and videos. There will exist a point in the future where 1) digital content produced by generative AI will be indistinguishable from…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Alexander Vilesov , Yuan Tian , Nader Sehatbakhsh , Achuta Kadambi

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

As AI-generated images proliferate across digital platforms, reliable detection methods have become critical for combating misinformation and maintaining content authenticity. While numerous deepfake detection methods have been proposed,…

Computer Vision and Pattern Recognition · Computer Science 2026-02-10 Simiao Ren , Yuchen Zhou , Xingyu Shen , Kidus Zewde , Tommy Duong , George Huang , Hatsanai , Tiangratanakul , Tsang , Ng , En Wei , Jiayu Xue

The rapid rise of generative AI has transformed music creation, with millions of users engaging in AI-generated music. Despite its popularity, concerns regarding copyright infringement, job displacement, and ethical implications have led to…

Sound · Computer Science 2025-06-25 Darius Afchar , Gabriel Meseguer-Brocal , Kamil Akesbi , Romain Hennequin

The rapid advancement of generative AI enables highly realistic synthetic videos, posing significant challenges for content authentication and raising urgent concerns about misuse. Existing detection methods often struggle with…

Computer Vision and Pattern Recognition · Computer Science 2026-02-05 Christian Internò , Robert Geirhos , Markus Olhofer , Sunny Liu , Barbara Hammer , David Klindt

AI-generated videos have achieved near-perfect visual realism (e.g., Sora), urgently necessitating reliable detection mechanisms. However, detecting such videos faces significant challenges in modeling high-dimensional spatiotemporal…

Computer Vision and Pattern Recognition · Computer Science 2025-10-10 Shuhai Zhang , ZiHao Lian , Jiahao Yang , Daiyuan Li , Guoxuan Pang , Feng Liu , Bo Han , Shutao Li , Mingkui Tan

With the recent advancements in generative modeling, the realism of deepfake content has been increasing at a steady pace, even reaching the point where people often fail to detect manipulated media content online, thus being deceived into…

The proliferation of AI-generated video models poses new challenges to information integrity and digital trust. A key confound, however, remains unaddressed: commercial generators embed visible overlay watermarks for provenance tracking,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Zhuo Wang , Xiliang Liu , Ligang Sun

Recent advancements in deep learning generative models have raised concerns as they can create highly convincing counterfeit images and videos. This poses a threat to people's integrity and can lead to social instability. To address this…

Computer Vision and Pattern Recognition · Computer Science 2024-02-19 Leandro A. Passos , Danilo Jodas , Kelton A. P. da Costa , Luis A. Souza Júnior , Douglas Rodrigues , Javier Del Ser , David Camacho , João Paulo Papa

Despite encouraging progress in deepfake detection, generalization to unseen forgery types remains a significant challenge due to the limited forgery clues explored during training. In contrast, we notice a common phenomenon in deepfake:…

Computer Vision and Pattern Recognition · Computer Science 2023-06-27 Jiazhi Guan , Hang Zhou , Mingming Gong , Errui Ding , Jingdong Wang , Youjian Zhao