English
Related papers

Related papers: GenWorld: Towards Detecting AI-generated Real-worl…

200 papers

Recently, video generation techniques have advanced rapidly. Given the popularity of video content on social media platforms, these models intensify concerns about the spread of fake information. Therefore, there is a growing demand for…

Computer Vision and Pattern Recognition · Computer Science 2024-08-23 Haoxing Chen , Yan Hong , Zizheng Huang , Zhuoer Xu , Zhangxuan Gu , Yaohui Li , Jun Lan , Huijia Zhu , Jianfu Zhang , Weiqiang Wang , Huaxiong Li

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 extraordinary ability of generative models to generate photographic images has intensified concerns about the spread of disinformation, thereby leading to the demand for detectors capable of distinguishing between AI-generated fake…

Computer Vision and Pattern Recognition · Computer Science 2023-06-27 Mingjian Zhu , Hanting Chen , Qiangyu Yan , Xudong Huang , Guanyu Lin , Wei Li , Zhijun Tu , Hailin Hu , Jie Hu , Yunhe Wang

Recent advances in generative modeling can create remarkably realistic synthetic videos, making it increasingly difficult for humans to distinguish them from real ones and necessitating reliable detection methods. However, two key…

Computer Vision and Pattern Recognition · Computer Science 2026-01-19 Long Ma , Zihao Xue , Yan Wang , Zhiyuan Yan , Jin Xu , Xiaorui Jiang , Haiyang Yu , Yong Liao , Zhen Bi

The rapid advancement of generative AI has revolutionized image creation, enabling high-quality synthesis from text prompts while raising critical challenges for media authenticity. We present Ai-GenBench, a novel benchmark designed to…

Computer Vision and Pattern Recognition · Computer Science 2025-12-17 Lorenzo Pellegrini , Davide Cozzolino , Serafino Pandolfini , Davide Maltoni , Matteo Ferrara , Luisa Verdoliva , Marco Prati , Marco Ramilli

Recent advances in Generative AI (GenAI) have led to significant improvements in the quality of generated visual content. As AI-generated visual content becomes increasingly indistinguishable from real content, the challenge of detecting…

Computer Vision and Pattern Recognition · Computer Science 2025-07-18 Keerthi Veeramachaneni , Praveen Tirupattur , Amrit Singh Bedi , Mubarak Shah

The advancement of generation models has led to the emergence of highly realistic artificial intelligence (AI)-generated videos. Malicious users can easily create non-existent videos to spread false information. This letter proposes an…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Jianfa Bai , Man Lin , Gang Cao

The generative model has made significant advancements in the creation of realistic videos, which causes security issues. However, this emerging risk has not been adequately addressed due to the absence of a benchmark dataset for…

Computer Vision and Pattern Recognition · Computer Science 2024-05-08 Peisong He , Leyao Zhu , Jiaxing Li , Shiqi Wang , Haoliang Li

Recent advancements in AI-based multimedia generation have enabled the creation of hyper-realistic images and videos, raising concerns about their potential use in spreading misinformation. The widespread accessibility of generative…

Computer Vision and Pattern Recognition · Computer Science 2025-04-30 Joy Battocchio , Stefano Dell'Anna , Andrea Montibeller , Giulia Boato

The development of AI-Generated Content (AIGC) has empowered the creation of remarkably realistic AI-generated videos, such as those involving Sora. However, the widespread adoption of these models raises concerns regarding potential…

Computer Vision and Pattern Recognition · Computer Science 2024-05-27 Lichuan Ji , Yingqi Lin , Zhenhua Huang , Yan Han , Xiaogang Xu , Jiafei Wu , Chong Wang , Zhe Liu

The proliferation of AI-Generated Content (AIGC), especially deepfake videos, poses a severe threat to social trust by enabling fraud, privacy violations and disinformation. Existing AI-generated video detection (AGVD) benchmarks focus on…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Xingming Liao , Meiyu Zeng , Canyu Chen , Nankai Lin , Zhuowei Wang , Aimin Yang

The escalating quality of video generated by advanced video generation methods results in new security challenges, while there have been few relevant research efforts: 1) There is no open-source dataset for generated video detection, 2) No…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Long Ma , Zhiyuan Yan , Qinglang Guo , Yong Liao , Haiyang Yu , Pengyuan Zhou

Synthetic video generation is progressing very rapidly. The latest models can produce very realistic high-resolution videos that are virtually indistinguishable from real ones. Although several video forensic detectors have been recently…

Computer Vision and Pattern Recognition · Computer Science 2025-11-07 Riccardo Corvi , Davide Cozzolino , Ekta Prashnani , Shalini De Mello , Koki Nagano , Luisa Verdoliva

With the rapid advancement of generative models, highly realistic image synthesis has posed new challenges to digital security and media credibility. Although AI-generated image detection methods have partially addressed these concerns, a…

Computer Vision and Pattern Recognition · Computer Science 2025-09-12 Chunxiao Li , Xiaoxiao Wang , Meiling Li , Boming Miao , Peng Sun , Yunjian Zhang , Xiangyang Ji , Yao Zhu

Deepfakes have raised significant concerns due to their potential to spread false information and compromise digital media integrity. Current deepfake detection models often struggle to generalize across a diverse range of deepfake…

Computer Vision and Pattern Recognition · Computer Science 2025-03-05 Deressa Wodajo Deressa , Hannes Mareen , Peter Lambert , Solomon Atnafu , Zahid Akhtar , Glenn Van Wallendael

In recent years, AI-generated videos have become increasingly realistic and sophisticated. Meanwhile, Large Vision-Language Models (LVLMs) have shown strong potential for detecting such content. However, existing evaluation protocols…

Computer Vision and Pattern Recognition · Computer Science 2026-03-20 Yueying Zou , Pei Pei Li , Zekun Li , Xinyu Guo , Xing Cui , Huaibo Huang , Ran He

World models aim to endow AI systems with the ability to represent, generate, and interact with dynamic environments in a coherent and temporally consistent manner. While recent video generation models have demonstrated impressive visual…

Video generation models, as one form of world models, have emerged as one of the most exciting frontiers in AI, promising agents the ability to imagine the future by modeling the temporal evolution of complex scenes. In autonomous driving,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Yang Zhou , Hao Shao , Letian Wang , Zhuofan Zong , Hongsheng Li , Steven L. Waslander

Recent generative models show impressive performance in generating photographic images. Humans can hardly distinguish such incredibly realistic-looking AI-generated images from real ones. AI-generated images may lead to ubiquitous…

Computer Vision and Pattern Recognition · Computer Science 2024-03-08 Nan Zhong , Yiran Xu , Sheng Li , Zhenxing Qian , Xinpeng Zhang

With the rapid advancement of autonomous driving technology, a lack of data has become a major obstacle to enhancing perception model accuracy. Researchers are now exploring controllable data generation using world models to diversify…

Computer Vision and Pattern Recognition · Computer Science 2025-06-27 Xinqing Li , Ruiqi Song , Qingyu Xie , Ye Wu , Nanxin Zeng , Yunfeng Ai
‹ Prev 1 2 3 10 Next ›