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Related papers: PhyWorld: Physics-Faithful World Model for Video G…

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Recent advances in world models have greatly enhanced interactive environment simulation. Existing methods mainly fall into two categories: (1) static world generation models, which construct 3D environments without active agents, and (2)…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Yitong Wang , Fangyun Wei , Hongyang Zhang , Bo Dai , Yan Lu

Modern generative video models excel at producing convincing, high-quality outputs, but struggle to maintain multi-view and spatiotemporal consistency in highly dynamic real-world environments. In this work, we introduce \textbf{AnyView}, a…

Evaluating robot control policies is difficult: real-world testing is costly, and handcrafted simulators require manual effort to improve in realism and generality. We propose a world-model-based policy evaluation environment (WorldGym), an…

Robotics · Computer Science 2025-10-01 Julian Quevedo , Ansh Kumar Sharma , Yixiang Sun , Varad Suryavanshi , Percy Liang , Sherry Yang

World simulation has gained increasing popularity due to its ability to model virtual environments and predict the consequences of actions. However, the limited temporal context window often leads to failures in maintaining long-term…

Computer Vision and Pattern Recognition · Computer Science 2026-01-05 Zeqi Xiao , Yushi Lan , Yifan Zhou , Wenqi Ouyang , Shuai Yang , Yanhong Zeng , Xingang Pan

Video generation techniques have achieved remarkable advancements in visual quality, yet faithfully reproducing real-world physics remains elusive. Preference-based model post-training may improve physical consistency, but requires costly…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Wenxu Qian , Chaoyue Wang , Hou Peng , Zhiyu Tan , Hao Li , Anxiang Zeng

World models predict state transitions in response to actions and are increasingly developed across diverse modalities. However, standard training objectives such as maximum likelihood estimation (MLE) often misalign with task-specific…

Machine Learning · Computer Science 2025-10-28 Jialong Wu , Shaofeng Yin , Ningya Feng , Mingsheng Long

Recent advancements in video generation have substantially improved visual quality and temporal coherence, making these models increasingly appealing for applications such as autonomous driving, particularly in the context of driving…

Computer Vision and Pattern Recognition · Computer Science 2025-08-25 Chun-Peng Chang , Chen-Yu Wang , Julian Schmidt , Holger Caesar , Alain Pagani

World models, especially in autonomous driving, are trending and drawing extensive attention due to their capacity for comprehending driving environments. The established world model holds immense potential for the generation of…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Xiaofeng Wang , Zheng Zhu , Guan Huang , Xinze Chen , Jiagang Zhu , Jiwen Lu

Intuitive physics understanding in video diffusion models plays an essential role in building general-purpose physically plausible world simulators, yet accurately evaluating such capacity remains a challenging task due to the difficulty in…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Jianhao Yuan , Fabio Pizzati , Francesco Pinto , Lars Kunze , Ivan Laptev , Paul Newman , Philip Torr , Daniele De Martini

The vision and language generative models have been overgrown in recent years. For video generation, various open-sourced models and public-available services have been developed to generate high-quality videos. However, these methods often…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Yaofang Liu , Xiaodong Cun , Xuebo Liu , Xintao Wang , Yong Zhang , Haoxin Chen , Yang Liu , Tieyong Zeng , Raymond Chan , Ying Shan

Pretrained foundation models have become an important basis for end-to-end autonomous driving. In contrast to vision-language models pretrained primarily on static image-text pairs, video generative models capture temporal dynamics and…

Computer Vision and Pattern Recognition · Computer Science 2026-05-28 Chen Shi , Jinrui Xu , Shaoshuai Shi , Kehua Sheng , Bo Zhang , Li Jiang

Generative models trained on internet data have revolutionized how text, image, and video content can be created. Perhaps the next milestone for generative models is to simulate realistic experience in response to actions taken by humans,…

Artificial Intelligence · Computer Science 2024-09-27 Sherry Yang , Yilun Du , Kamyar Ghasemipour , Jonathan Tompson , Leslie Kaelbling , Dale Schuurmans , Pieter Abbeel

Current video diffusion models generate visually compelling content but often violate basic laws of physics, producing subtle artifacts like rubber-sheet deformations and inconsistent object motion. We introduce a frequency-domain physics…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Bowen Xue , Giuseppe Claudio Guarnera , Shuang Zhao , Zahra Montazeri

We present Waver, a high-performance foundation model for unified image and video generation. Waver can directly generate videos with durations ranging from 5 to 10 seconds at a native resolution of 720p, which are subsequently upscaled to…

Computer Vision and Pattern Recognition · Computer Science 2025-08-27 Yifu Zhang , Hao Yang , Yuqi Zhang , Yifei Hu , Fengda Zhu , Chuang Lin , Xiaofeng Mei , Yi Jiang , Bingyue Peng , Zehuan Yuan

Imitation learning has emerged as a promising approach towards building generalist robots. However, scaling imitation learning for large robot foundation models remains challenging due to its reliance on high-quality expert demonstrations.…

Robotics · Computer Science 2025-05-26 Chuning Zhu , Raymond Yu , Siyuan Feng , Benjamin Burchfiel , Paarth Shah , Abhishek Gupta

Synthesizing physics-grounded 3D assets is a critical bottleneck for interactive virtual worlds and embodied AI. Existing methods predominantly focus on static geometry, overlooking the functional properties essential for interaction. We…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Yunhan Yang , Chunshi Wang , Junliang Ye , Yang Li , Zanxin Chen , Zehuan Huang , Yao Mu , Zhuo Chen , Chunchao Guo , Xihui Liu

Web agents require massive trajectories to generalize, yet real-world training is constrained by network latency, rate limits, and safety risks. We introduce \textbf{WebWorld} series, the first open-web simulator trained at scale. While…

Artificial Intelligence · Computer Science 2026-02-17 Zikai Xiao , Jianhong Tu , Chuhang Zou , Yuxin Zuo , Zhi Li , Peng Wang , Bowen Yu , Fei Huang , Junyang Lin , Zuozhu Liu

With the rapid development of AI-generated content (AIGC), video generation has emerged as one of its most dynamic and impactful subfields. In particular, the advancement of video generation foundation models has led to growing demand for…

Video generation models have made significant progress in generating realistic content, enabling applications in simulation, gaming, and film making. However, current generated videos still contain visual artifacts arising from 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Duolikun Danier , Ge Gao , Steven McDonagh , Changjian Li , Hakan Bilen , Oisin Mac Aodha

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