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

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Realistic simulation of dynamic scenes requires accurately capturing diverse material properties and modeling complex object interactions grounded in physical principles. However, existing methods are constrained to basic material types…

Computer Vision and Pattern Recognition · Computer Science 2025-05-09 Zhuoman Liu , Weicai Ye , Yan Luximon , Pengfei Wan , Di Zhang

Recent advancements in human video synthesis have enabled the generation of high-quality videos through the application of stable diffusion models. However, existing methods predominantly concentrate on animating solely the human element…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Jinlin Liu , Kai Yu , Mengyang Feng , Xiefan Guo , Miaomiao Cui

Interactive world models continually generate video by responding to a user's actions, enabling open-ended generation capabilities. However, existing models typically lack a 3D representation of the environment, meaning 3D consistency must…

Computer Vision and Pattern Recognition · Computer Science 2026-03-05 Samuel Garcin , Thomas Walker , Steven McDonagh , Tim Pearce , Hakan Bilen , Tianyu He , Kaixin Wang , Jiang Bian

Traditional fluid dynamics simulation pipelines combine numerical solvers with rendering, producing highly realistic results but at considerable computational cost. Diffusion-based generative video models offer a faster alternative, yet…

Graphics · Computer Science 2026-03-18 Yang Bai , George Eskandar , Ziyuan Liu , Gitta Kutyniok

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

Continual learning refers to the ability of humans and animals to incrementally learn over time in a given environment. Trying to simulate this learning process in machines is a challenging task, also due to the inherent difficulty in…

Computer Vision and Pattern Recognition · Computer Science 2021-09-17 Enrico Meloni , Alessandro Betti , Lapo Faggi , Simone Marullo , Matteo Tiezzi , Stefano Melacci

Recent advances in generative video modeling, driven by large-scale datasets and powerful architectures, have yielded remarkable visual realism. However, emerging evidence suggests that simply scaling data and model size does not endow…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Ying Shen , Jerry Xiong , Tianjiao Yu , Ismini Lourentzou

World models empower model-based agents to interactively explore, reason, and plan within imagined environments for real-world decision-making. However, the high demand for interactivity poses challenges in harnessing recent advancements in…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Jialong Wu , Shaofeng Yin , Ningya Feng , Xu He , Dong Li , Jianye Hao , Mingsheng Long

Commercial video generation systems such as Seedance2.0 and Veo3.1 have rapidly improved, strengthening the view that video generators may be evolving into "world simulators." Yet the community still lacks a benchmark that directly tests…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Keming Wu , Yijing Cui , Wenhan Xue , Qijie Wang , Xuan Luo , Zhiyuan Feng , Zuhao Yang , Sudong Wang , Sicong Jiang , Haowei Zhu , Zihan Wang , Ping Nie , Wenhu Chen , Bin Wang

A world model enables an intelligent agent to imagine, predict, and reason about how the world evolves in response to its actions, and accordingly to plan and strategize. While recent video generation models produce realistic visual…

Diffusion models have significantly improved the performance of image editing. Existing methods realize various approaches to achieve high-quality image editing, including but not limited to text control, dragging operation, and…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Ling Yang , Bohan Zeng , Jiaming Liu , Hong Li , Minghao Xu , Wentao Zhang , Shuicheng Yan

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

Recent video generation models demonstrate impressive synthesis capabilities but remain limited by single-modality conditioning, constraining their holistic world understanding. This stems from insufficient cross-modal interaction and…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Jiehui Huang , Yuechen Zhang , Xu He , Yuan Gao , Zhi Cen , Bin Xia , Yan Zhou , Xin Tao , Pengfei Wan , Jiaya Jia

Generating visual instructions in a given context is essential for developing interactive world simulators. While prior works address this problem through either text-guided image manipulation or video prediction, these tasks are typically…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Yujiang Pu , Zhanbo Huang , Vishnu Boddeti , Yu Kong

Text- and image-conditioned video generation models have achieved strong visual fidelity and temporal coherence, but they often fail to generate motion governed by kinematic and geometric constraints. In these settings, object parts must…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Rahul Jain , Mayank Patel , Asim Unmesh , Karthik Ramani

World-Action Models (WAM) initialized from pre-trained video generation backbones have demonstrated remarkable potential for robot policy learning. However, existing approaches face two critical bottlenecks that hinder performance and…

Building video world models upon pretrained video generation systems represents an important yet challenging step toward general spatiotemporal intelligence. A world model should possess three essential properties: controllability,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Jianxiong Gao , Zhaoxi Chen , Xian Liu , Junhao Zhuang , Chengming Xu , Jianfeng Feng , Yu Qiao , Yanwei Fu , Chenyang Si , Ziwei Liu

We present a video generation model that accurately reproduces object motion, changes in camera viewpoint, and new content that arises over time. Existing video generation methods often fail to produce new content as a function of time…

Computer Vision and Pattern Recognition · Computer Science 2022-06-10 Tim Brooks , Janne Hellsten , Miika Aittala , Ting-Chun Wang , Timo Aila , Jaakko Lehtinen , Ming-Yu Liu , Alexei A. Efros , Tero Karras

Modeling sounds emitted from physical object interactions is critical for immersive perceptual experiences in real and virtual worlds. Traditional methods of impact sound synthesis use physics simulation to obtain a set of physics…

Computer Vision and Pattern Recognition · Computer Science 2023-07-11 Kun Su , Kaizhi Qian , Eli Shlizerman , Antonio Torralba , Chuang Gan

Despite recent progress in video generation, producing videos that adhere to physical laws remains a significant challenge. Traditional diffusion-based methods struggle to extrapolate to unseen physical conditions (eg, velocity) due to…

Computer Vision and Pattern Recognition · Computer Science 2025-04-23 Wang Lin , Liyu Jia , Wentao Hu , Kaihang Pan , Zhongqi Yue , Wei Zhao , Jingyuan Chen , Fei Wu , Hanwang Zhang