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Video--based world models have emerged along two dominant paradigms: video generation and 3D reconstruction. However, existing evaluation benchmarks either focus narrowly on visual fidelity and text--video alignment for generative models,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Meiqi Wu , Zhixin Cai , Fufangchen Zhao , Xiaokun Feng , Rujing Dang , Bingze Song , Ruitian Tian , Jiashu Zhu , Jiachen Lei , Hao Dou , Jing Tang , Lei Sun , Jiahong Wu , Xiangxiang Chu , Zeming Liu , Kaiqi Huang

Achieving Artificial General Intelligence (AGI) requires agents that learn and interact adaptively, with interactive world models providing scalable environments for perception, reasoning, and action. Yet current research still lacks…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Jianjie Fang , Yingshan Lei , Qin Wan , Ziyou Wang , Yuchao Huang , Yongyan Xu , Baining Zhao , Weichen Zhang , Chen Gao , Xinlei Chen , Yong Li

Recent advances in generative foundational models, often termed "world models," have propelled interest in applying them to critical tasks like robotic planning and autonomous system training. For reliable deployment, these models must…

Computer Vision and Pattern Recognition · Computer Science 2026-01-30 Rishi Upadhyay , Howard Zhang , Jim Solomon , Ayush Agrawal , Pranay Boreddy , Shruti Satya Narayana , Yunhao Ba , Alex Wong , Celso M de Melo , Achuta Kadambi

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

World Generation Models are emerging as a cornerstone of next-generation multimodal intelligence systems. Unlike traditional 2D visual generation, World Models aim to construct realistic, dynamic, and physically consistent 3D/4D worlds from…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Yiting Lu , Wei Luo , Peiyan Tu , Haoran Li , Hanxin Zhu , Zihao Yu , Xingrui Wang , Xinyi Chen , Xinge Peng , Xin Li , Zhibo Chen

Video generation models have achieved remarkable progress in creating high-quality, photorealistic content. However, their ability to accurately simulate physical phenomena remains a critical and unresolved challenge. This paper presents…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Jing Gu , Xian Liu , Yu Zeng , Ashwin Nagarajan , Fangrui Zhu , Daniel Hong , Yue Fan , Qianqi Yan , Kaiwen Zhou , Ming-Yu Liu , Xin Eric Wang

In different multimodal scenarios, it needs to integrate and utilize information across modalities in a specific way based on the demands of the task. Different integration ways between modalities are referred to as "multimodal…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Yu Miao , Zequn Yang , Yake Wei , Ziheng Chen , Haotian Ni , Haodong Duan , Kai Chen , Di Hu

Significant progress has been made in the field of Instruction-based Image Editing (IIE). However, evaluating these models poses a significant challenge. A crucial requirement in this field is the establishment of a comprehensive evaluation…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Yiwei Ma , Jiayi Ji , Ke Ye , Weihuang Lin , Zhibin Wang , Yonghan Zheng , Qiang Zhou , Xiaoshuai Sun , Rongrong Ji

Interactive video generation models such as Genie, YUME, HY-World, and Matrix-Game are advancing rapidly, yet every model is evaluated on its own benchmark with private scenes and trajectories, making fair cross-model comparison impossible.…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Xiaojie Xu , Zhengyuan Lin , Kang He , Yukang Feng , Xiaofeng Mao , Yuanyang Yin , Kaipeng Zhang , Yongtao Ge

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

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

This paper presents ConvBench, a novel multi-turn conversation evaluation benchmark tailored for Large Vision-Language Models (LVLMs). Unlike existing benchmarks that assess individual capabilities in single-turn dialogues, ConvBench adopts…

Multimedia · Computer Science 2024-04-26 Shuo Liu , Kaining Ying , Hao Zhang , Yue Yang , Yuqi Lin , Tianle Zhang , Chuanhao Li , Yu Qiao , Ping Luo , Wenqi Shao , Kaipeng Zhang

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

Instruction-guided video editing has emerged as a rapidly advancing research direction, offering new opportunities for intuitive content transformation while also posing significant challenges for systematic evaluation. Existing video…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Yinan Chen , Jiangning Zhang , Teng Hu , Yuxiang Zeng , Zhucun Xue , Qingdong He , Chengjie Wang , Yong Liu , Xiaobin Hu , Shuicheng Yan

The recent development of Multimodal Large Language Models (MLLMs) has significantly advanced AI's ability to understand visual modalities. However, existing evaluation benchmarks remain limited to single-turn question answering,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-09 Yaning Pan , Qianqian Xie , Guohui Zhang , Zekun Wang , Yongqian Wen , Yuanxing Zhang , Haoxuan Hu , Zhiyu Pan , Yibing Huang , Zhidong Gan , Yonghong Lin , An Ping , Shihao Li , Yanghai Wang , Tianhao Peng , Jiaheng Liu

Rapid advances in multimodal models demand benchmarks that rigorously evaluate understanding and reasoning in safety-critical, dynamic real-world settings. We present AccidentBench, a large-scale benchmark that combines vehicle accident…

Recently advancements in large multimodal models have led to significant strides in image comprehension capabilities. Despite these advancements, there is a lack of the robust benchmark specifically for assessing the Image-to-Web conversion…

Computation and Language · Computer Science 2025-12-04 Hongcheng Guo , Wei Zhang , Junhao Chen , Yaonan Gu , Jian Yang , Junjia Du , Shaosheng Cao , Binyuan Hui , Tianyu Liu , Jianxin Ma , Chang Zhou , Zhoujun Li

Today's driving world models can generate remarkably realistic dash-cam videos, yet no single model excels universally. Some generate photorealistic textures but violate basic physics; others maintain geometric consistency but fail when…

Real-world video editing demands not only expert knowledge of cinematic techniques but also multimodal reasoning to select, align, and combine footage into coherent narratives. While recent Large Multimodal Models (LMMs) have shown…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Andong Deng , Dawei Du , Zhenfang Chen , Wen Zhong , Fan Chen , Guang Chen , Chia-Wen Kuo , Longyin Wen , Chen Chen , Sijie Zhu

Recent advancements in image generation models have enabled the prediction of future Graphical User Interface (GUI) states based on user instructions. However, existing benchmarks primarily focus on general domain visual fidelity, leaving…

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