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World models based on video generation demonstrate remarkable potential for simulating interactive environments but face persistent difficulties in two key areas: maintaining long-term content consistency when scenes are revisited and…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Tianxing Xu , Zixuan Wang , Guangyuan Wang , Li Hu , Zhongyi Zhang , Peng Zhang , Bang Zhang , Song-Hai Zhang

Modeling scenes using video generation models has garnered growing research interest in recent years. However, most existing approaches rely on perspective video models that synthesize only limited observations of a scene, leading to issues…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Yuheng Liu , Xin Lin , Xinke Li , Baihan Yang , Chen Wang , Kalyan Sunkavalli , Yannick Hold-Geoffroy , Hao Tan , Kai Zhang , Xiaohui Xie , Zifan Shi , Yiwei Hu

Scaling generative inverse and forward rendering to real-world scenarios is bottlenecked by the limited realism and temporal coherence of existing synthetic datasets. To bridge this persistent domain gap, we introduce a large-scale, dynamic…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Zheng-Hui Huang , Zhixiang Wang , Jiaming Tan , Ruihan Yu , Yidan Zhang , Bo Zheng , Yu-Lun Liu , Yung-Yu Chuang , Kaipeng Zhang

The ability to simulate the effects of future actions on the world is a crucial ability of intelligent embodied agents, enabling agents to anticipate the effects of their actions and make plans accordingly. While a large body of existing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-12 Siyuan Zhou , Yilun Du , Yuncong Yang , Lei Han , Peihao Chen , Dit-Yan Yeung , Chuang Gan

The integration of Vision-Language-Action (VLA) models with World Models has gained increasing attention. One representative approach treats learned World Models as generative simulators, enabling policy optimization entirely within…

Computer Vision and Pattern Recognition · Computer Science 2026-05-11 Jiaxuan Gao , Yongjian Guo , Zhong Guan , Wen Huang , Wanlun Ma , Xi Xiao , Junwu Xiong , Sheng Wen

The scalability of embodied intelligence is fundamentally constrained by the scarcity of real-world interaction data. While simulation platforms provide a promising alternative, existing approaches often suffer from a substantial visual and…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Zhengqing Gao , Ziwen Li , Xin Wang , Jiaxin Huang , Zhenyang Ren , Mingkai Shao , Hanlue Zhang , Tianyu Huang , Yongkang Cheng , Yandong Guo , Runqi Lin , Yuanyuan Wang , Tongliang Liu , Kun Zhang , Mingming Gong

Scalable sensor simulation is an important yet challenging open problem for safety-critical domains such as self-driving. Current works in image simulation either fail to be photorealistic or do not model the 3D environment and the dynamic…

Computer Vision and Pattern Recognition · Computer Science 2021-05-18 Yun Chen , Frieda Rong , Shivam Duggal , Shenlong Wang , Xinchen Yan , Sivabalan Manivasagam , Shangjie Xue , Ersin Yumer , Raquel Urtasun

Novel-view synthesis techniques achieve impressive results for static scenes but struggle when faced with the inconsistencies inherent to casual capture settings: varying illumination, scene motion, and other unintended effects that are…

Embodied AI requires agents that perceive, act, and anticipate how actions reshape future world states. World models serve as internal simulators that capture environment dynamics, enabling forward and counterfactual rollouts to support…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Xinqing Li , Xin He , Le Zhang , Min Wu , Xiaoli Li , Yun Liu

World models are central to LLM agents that must evaluate actions over long horizons. Yet much existing work focuses on environments governed by physical dynamics or spatial structure, whereas many high-impact domains, including supply…

Artificial Intelligence · Computer Science 2026-05-22 Zheyu Chen , Huiteng Zhuang , Zhuohuan Li , Chuanhao Li

Recent approaches have demonstrated the promise of using diffusion models to generate interactive and explorable worlds. However, most of these methods face critical challenges such as excessively large parameter sizes, reliance on lengthy…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Xiaofeng Mao , Zhen Li , Chuanhao Li , Xiaojie Xu , Kaining Ying , Tong He , Jiangmiao Pang , Yu Qiao , Kaipeng Zhang

Humans possess a remarkable ability to mentally explore and replay 3D environments they have previously experienced. Inspired by this mental process, we present EvoWorld: a world model that bridges panoramic video generation with evolving…

Computer Vision and Pattern Recognition · Computer Science 2025-10-02 Jiahao Wang , Luoxin Ye , TaiMing Lu , Junfei Xiao , Jiahan Zhang , Yuxiang Guo , Xijun Liu , Rama Chellappa , Cheng Peng , Alan Yuille , Jieneng Chen

Despite impressive progress in video generation, existing models remain limited to surface-level plausibility, lacking a coherent and unified understanding of the world. Prior approaches typically incorporate only a single form of…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Boming Tan , Xiangdong Zhang , Ning Liao , Yuqing Zhang , Shaofeng Zhang , Xue Yang , Qi Fan , Yanyong Zhang

World models (WMs) demonstrate strong capabilities in prediction, generation, and planning tasks. Existing WMs primarily focus on unstructured data and cannot leverage the ubiquitous structured data, often represented as graphs, in the…

Machine Learning · Computer Science 2025-07-15 Tao Feng , Yexin Wu , Guanyu Lin , Jiaxuan You

Generative video models, a leading approach to world modeling, face fundamental limitations. They often violate physical and logical rules, lack interactivity, and operate as opaque black boxes ill-suited for building structured, queryable…

Computer Vision and Pattern Recognition · Computer Science 2025-12-15 Felix O'Mahony , Roberto Cipolla , Ayush Tewari

Recent progress in 3D reconstruction has made it easy to create realistic digital twins from everyday environments. However, current digital twins remain largely static and are limited to navigation and view synthesis without embodied…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Byungjun Kim , Taeksoo Kim , Junyoung Lee , Hanbyul Joo

We propose to build realistic virtual worlds, called 360RVW, for large urban environments directly from 360{\deg} videos. We provide an interface for interactive exploration, where users can freely navigate via their own avatars. 360{\deg}…

Multimedia · Computer Science 2025-10-14 Mizuki Takenawa , Naoki Sugimoto , Leslie Wöhler , Satoshi Ikehata , Kiyoharu Aizawa

Recent video foundation models demonstrate impressive visual synthesis but frequently suffer from geometric inconsistencies. While existing methods attempt to inject 3D priors via architectural modifications, they often incur high…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Weijie Wang , Xiaoxuan He , Youping Gu , Yifan Yang , Zeyu Zhang , Yefei He , Yanbo Ding , Xirui Hu , Donny Y. Chen , Zhiyuan He , Yuqing Yang , Bohan Zhuang

World models are a powerful paradigm in AI and robotics, enabling agents to reason about the future by predicting visual observations or compact latent states. The 1X World Model Challenge introduces an open-source benchmark of real-world…

Machine Learning · Computer Science 2025-10-09 Riccardo Mereu , Aidan Scannell , Yuxin Hou , Yi Zhao , Aditya Jitta , Antonio Dominguez , Luigi Acerbi , Amos Storkey , Paul Chang

In autonomous driving, predicting future events in advance and evaluating the foreseeable risks empowers autonomous vehicles to better plan their actions, enhancing safety and efficiency on the road. To this end, we propose Drive-WM, the…

Computer Vision and Pattern Recognition · Computer Science 2023-11-30 Yuqi Wang , Jiawei He , Lue Fan , Hongxin Li , Yuntao Chen , Zhaoxiang Zhang