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Video generation has witnessed significant advancements, yet evaluating these models remains a challenge. A comprehensive evaluation benchmark for video generation is indispensable for two reasons: 1) Existing metrics do not fully align…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Ziqi Huang , Yinan He , Jiashuo Yu , Fan Zhang , Chenyang Si , Yuming Jiang , Yuanhan Zhang , Tianxing Wu , Qingyang Jin , Nattapol Chanpaisit , Yaohui Wang , Xinyuan Chen , Limin Wang , Dahua Lin , Yu Qiao , Ziwei Liu

Recent advances in large-scale video world models have enabled increasingly realistic future prediction, raising the prospect of using generated videos as scalable supervision for robot learning. However, for embodied manipulation,…

Video generation has witnessed significant advancements, yet evaluating these models remains a challenge. A comprehensive evaluation benchmark for video generation is indispensable for two reasons: 1) Existing metrics do not fully align…

Computer Vision and Pattern Recognition · Computer Science 2024-11-21 Ziqi Huang , Fan Zhang , Xiaojie Xu , Yinan He , Jiashuo Yu , Ziyue Dong , Qianli Ma , Nattapol Chanpaisit , Chenyang Si , Yuming Jiang , Yaohui Wang , Xinyuan Chen , Ying-Cong Chen , Limin Wang , Dahua Lin , Yu Qiao , Ziwei Liu

Recent advances in creative AI have enabled the synthesis of high-fidelity images and videos conditioned on language instructions. Building on these developments, text-to-video diffusion models have evolved into embodied world models (EWMs)…

Robotics · Computer Science 2025-05-20 Hu Yue , Siyuan Huang , Yue Liao , Shengcong Chen , Pengfei Zhou , Liliang Chen , Maoqing Yao , Guanghui Ren

Video generation assessment is essential for ensuring that generative models produce visually realistic, high-quality videos while aligning with human expectations. Current video generation benchmarks fall into two main categories:…

Computer Vision and Pattern Recognition · Computer Science 2025-04-30 Hui Han , Siyuan Li , Jiaqi Chen , Yiwen Yuan , Yuling Wu , Chak Tou Leong , Hanwen Du , Junchen Fu , Youhua Li , Jie Zhang , Chi Zhang , Li-jia Li , Yongxin Ni

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

Recent text-to-video generation models have made remarkable progress in visual realism, motion fidelity, and text-video alignment, yet they still struggle to produce socially coherent behavior. Unlike humans, who readily infer intentions,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Wenshuo Peng , Gongxuan Wang , Tianmeng Yang , Chuanhao Li , Xiaojie Xu , Hui He , Kaipeng Zhang

Recent advancements in predictive models have demonstrated exceptional capabilities in predicting the future state of objects and scenes. However, the lack of categorization based on inherent characteristics continues to hinder the progress…

Computer Vision and Pattern Recognition · Computer Science 2024-10-24 Yiran Qin , Zhelun Shi , Jiwen Yu , Xijun Wang , Enshen Zhou , Lijun Li , Zhenfei Yin , Xihui Liu , Lu Sheng , Jing Shao , Lei Bai , Wanli Ouyang , Ruimao Zhang

Recent advances in video generation have been remarkable, enabling models to produce visually compelling videos with synchronized audio. While existing video generation benchmarks provide comprehensive metrics for visual quality, they lack…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Daili Hua , Xizhi Wang , Bohan Zeng , Xinyi Huang , Hao Liang , Junbo Niu , Xinlong Chen , Quanqing Xu , Wentao Zhang

The evolution of video generation toward complex, multi-shot narratives has exposed a critical deficit in current evaluation methods. Existing benchmarks remain anchored to single-shot paradigms, lacking the comprehensive story assets and…

Multimedia · Computer Science 2026-03-02 Haoyuan Shi , Yunxin Li , Nanhao Deng , Zhenran Xu , Xinyu Chen , Longyue Wang , Baotian Hu , Min Zhang

Recent progress in generative video models, such as Veo-3, has shown surprising zero-shot reasoning abilities, creating a growing need for systematic and reliable evaluation. We introduce V-ReasonBench, a benchmark designed to assess video…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Yang Luo , Xuanlei Zhao , Baijiong Lin , Lingting Zhu , Liyao Tang , Yuqi Liu , Ying-Cong Chen , Shengju Qian , Xin Wang , Yang You

Video generation has advanced significantly, evolving from producing unrealistic outputs to generating videos that appear visually convincing and temporally coherent. To evaluate these video generative models, benchmarks such as VBench have…

Computer Vision and Pattern Recognition · Computer Science 2025-08-21 Dian Zheng , Ziqi Huang , Hongbo Liu , Kai Zou , Yinan He , Fan Zhang , Lulu Gu , Yuanhan Zhang , Jingwen He , Wei-Shi Zheng , Yu Qiao , Ziwei Liu

Video foundation models aim to integrate video understanding, generation, editing, and instruction following within a single framework, making them a central direction for next-generation multimodal systems. However, existing evaluation…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Jianhui Wei , Xiaotian Zhang , Yichen Li , Yuan Wang , Yan Zhang , Ziyi Chen , Zhihang Tang , Wei Xu , Zuozhu Liu

Video generation has advanced rapidly, improving evaluation methods, yet assessing video's motion remains a major challenge. Specifically, there are two key issues: 1) current motion metrics do not fully align with human perceptions; 2) the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Xinran Ling , Chen Zhu , Meiqi Wu , Hangyu Li , Xiaokun Feng , Cundian Yang , Aiming Hao , Jiashu Zhu , Jiahong Wu , Xiangxiang Chu

Video generation has advanced rapidly, with recent methods producing increasingly convincing animated results. However, existing benchmarks-largely designed for realistic videos-struggle to evaluate animation-style generation with its…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Leyi Wu , Pengjun Fang , Kai Sun , Yazhou Xing , Yinwei Wu , Songsong Wang , Ziqi Huang , Dan Zhou , Yingqing He , Ying-Cong Chen , Qifeng Chen

Video generation models have rapidly progressed, positioning themselves as video world models capable of supporting decision-making applications like robotics and autonomous driving. However, current benchmarks fail to rigorously evaluate…

Computer Vision and Pattern Recognition · Computer Science 2025-03-03 Dacheng Li , Yunhao Fang , Yukang Chen , Shuo Yang , Shiyi Cao , Justin Wong , Michael Luo , Xiaolong Wang , Hongxu Yin , Joseph E. Gonzalez , Ion Stoica , Song Han , Yao Lu

Building robots that can perceive, reason, and act in dynamic, unstructured environments remains a core challenge. Recent embodied systems often adopt a dual-system paradigm, where System 2 handles high-level reasoning while System 1…

Video generation models have made significant progress in simulating future states, showcasing their potential as world simulators in embodied scenarios. However, existing models often lack robust understanding, limiting their ability to…

Computer Vision and Pattern Recognition · Computer Science 2025-06-11 Xiaowei Chi , Chun-Kai Fan , Hengyuan Zhang , Xingqun Qi , Rongyu Zhang , Anthony Chen , Chi-min Chan , Wei Xue , Qifeng Liu , Shanghang Zhang , Yike Guo

The next frontier for video generation lies in developing models capable of zero-shot reasoning, where understanding real-world scientific laws is crucial for accurate physical outcome modeling under diverse conditions. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Lanxiang Hu , Abhilash Shankarampeta , Yixin Huang , Zilin Dai , Haoyang Yu , Yujie Zhao , Haoqiang Kang , Daniel Zhao , Tajana Rosing , Hao Zhang

Rapid advances in audio-video (AV) generation have enabled high-fidelity synthesis with synchronized sound, particularly for human-related scenarios involving speech and interactions. Yet evaluation for AV generation remains at an early…

Artificial Intelligence · Computer Science 2026-05-26 Jialiang Yang , Bin Xia , Ruihang Chu , Dingdong Wang , Wanke Xia , Zhun Mou , Tianyang Zhong , Yiting Zhao , Wenming Yang
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