English
Related papers

Related papers: DeMamba: AI-Generated Video Detection on Million-S…

200 papers

Addressing the dual challenges of local redundancy and global dependencies in video understanding, this work innovatively adapts the Mamba to the video domain. The proposed VideoMamba overcomes the limitations of existing 3D convolution…

Computer Vision and Pattern Recognition · Computer Science 2024-03-13 Kunchang Li , Xinhao Li , Yi Wang , Yinan He , Yali Wang , Limin Wang , Yu Qiao

Due to the widespread use of smartphones with high-quality digital cameras and easy access to a wide range of software apps for recording, editing, and sharing videos and images, as well as the deep learning AI platforms, a new phenomenon…

Computer Vision and Pattern Recognition · Computer Science 2023-09-08 Nikhil Sontakke , Sejal Utekar , Shivansh Rastogi , Shriraj Sonawane

Although 3D generated content (3DGC) offers advantages in reducing production costs and accelerating design timelines, its quality often falls short when compared to 3D professionally generated content. Common quality issues frequently…

Image and Video Processing · Electrical Eng. & Systems 2024-09-13 Yingjie Zhou , Zicheng Zhang , Farong Wen , Jun Jia , Yanwei Jiang , Xiaohong Liu , Xiongkuo Min , Guangtao Zhai

Deepfake technology, derived from deep learning, seamlessly inserts individuals into digital media, irrespective of their actual participation. Its foundation lies in machine learning and Artificial Intelligence (AI). Initially, deepfakes…

Computer Vision and Pattern Recognition · Computer Science 2024-04-22 Gazi Hasin Ishrak , Zalish Mahmud , MD. Zami Al Zunaed Farabe , Tahera Khanom Tinni , Tanzim Reza , Mohammad Zavid Parvez

AI-generated synthetic media, also called Deepfakes, have significantly influenced so many domains, from entertainment to cybersecurity. Generative Adversarial Networks (GANs) and Diffusion Models (DMs) are the main frameworks used to…

Existing text-to-video retrieval benchmarks are dominated by real-world footage where much of the semantics can be inferred from a single frame, leaving temporal reasoning and explicit end-state grounding under-evaluated. We introduce…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Minghan Li , Tongna Chen , Tianrui Lv , Yishuai Zhang , Suchao An , Guodong Zhou

AI-generated media are advancing rapidly, raising pressing concerns for content authenticity and digital trust. We introduce DYMAPIA, a multi-domain Deepfake detection framework that fuses spatial, spectral, and temporal cues to capture…

Computer Vision and Pattern Recognition · Computer Science 2026-04-28 Md Shohel Rana , Andrew H. Sung

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

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

The recent surge in advanced generative models, such as diffusion models and generative adversarial networks (GANs), has led to an alarming rise in AI-generated images across various domains on the web. While such technologies offer…

Computer Vision and Pattern Recognition · Computer Science 2025-05-09 Jocelyn Dzuong

Recently, state space models (SSM), particularly Mamba, have attracted significant attention from scholars due to their ability to effectively balance computational efficiency and performance. However, most existing visual Mamba methods…

Computer Vision and Pattern Recognition · Computer Science 2025-04-09 Leiye Liu , Miao Zhang , Jihao Yin , Tingwei Liu , Wei Ji , Yongri Piao , Huchuan Lu

The rapid advancement in deep learning makes the differentiation of authentic and manipulated facial images and video clips unprecedentedly harder. The underlying technology of manipulating facial appearances through deep generative…

Computer Vision and Pattern Recognition · Computer Science 2021-09-08 Sm Zobaed , Md Fazle Rabby , Md Istiaq Hossain , Ekram Hossain , Sazib Hasan , Asif Karim , Khan Md. Hasib

As deep learning technology continues to evolve, the images yielded by generative models are becoming more and more realistic, triggering people to question the authenticity of images. Existing generated image detection methods detect…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Xiuli Bi , Bo Liu , Fan Yang , Bin Xiao , Weisheng Li , Gao Huang , Pamela C. Cosman

With generative models becoming increasingly sophisticated and diverse, detecting AI-generated images has become increasingly challenging. While existing AI-genereted Image detectors achieve promising performance on in-distribution…

Computer Vision and Pattern Recognition · Computer Science 2026-01-26 Haozhen Yan , Yan Hong , Suning Lang , Jiahui Zhan , Yikun Ji , Yujie Gao , Huijia Zhu , Jun Lan , Jianfu Zhang

The recent advancements in Text-to-Video Artificial Intelligence Generated Content (AIGC) have been remarkable. Compared with traditional videos, the assessment of AIGC videos encounters various challenges: visual inconsistency that defy…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Bowen Qu , Xiaoyu Liang , Shangkun Sun , Wei Gao

Artificial Intelligence (AI)-generated images have become increasingly realistic and readily adaptable to concrete real-world claims, creating new challenges for verifying visual evidence. A concrete emerging risk is AI-generated refund…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Xinyu Yan , Boyang Chen , Jiaming Zhang , Tiantong Wu , Hong Xi Tae , Yichen He , Tiantong Wang , Yachun Mi , Yurong Hao , Yilei Zhao , Lei Xiao , Longtao Huang , Pengjun Xie , Wei Liu , Wei Yang Bryan Lim

Over the past decade, there has been tremendous progress in creating synthetic media, mainly thanks to the development of powerful methods based on generative adversarial networks (GAN). Very recently, methods based on diffusion models (DM)…

Computer Vision and Pattern Recognition · Computer Science 2022-11-03 Riccardo Corvi , Davide Cozzolino , Giada Zingarini , Giovanni Poggi , Koki Nagano , Luisa Verdoliva

Recent advances in AI-generated content have fueled the rise of highly realistic synthetic videos, posing severe risks to societal trust and digital integrity. Existing benchmarks for video authenticity detection typically suffer from…

Computer Vision and Pattern Recognition · Computer Science 2025-08-15 Jieyu Li , Xin Zhang , Joey Tianyi Zhou

The rise of deepfake technology brings forth new questions about the authenticity of various forms of media found online today. Videos and images generated by artificial intelligence (AI) have become increasingly more difficult to…

Computer Vision and Pattern Recognition · Computer Science 2025-07-28 Benjamin Carter , Nathan Dilla , Micheal Callahan , Atuhaire Ambala

Recent advances in deep learning have led to substantial improvements in deepfake generation, resulting in fake media with a more realistic appearance. Although deepfake media have potential application in a wide range of areas and are…

Computer Vision and Pattern Recognition · Computer Science 2022-02-15 Trung-Nghia Le , Huy H Nguyen , Junichi Yamagishi , Isao Echizen