English
Related papers

Related papers: LivingWorld: Interactive 4D World Generation with …

200 papers

World models have made significant progress in modeling dynamic environments; however, most embodied world models are still restricted to 2D representations, lacking the comprehensive multi-view information essential for embodied spatial…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Peiyan Tu , Hanxin Zhu , Jingwen Sun , Shaojie Ren , Cong Wang , Jiayi Luo , Xiaoqian Cheng , Zhibo Chen

Recent advances in illumination control extend image-based methods to video, yet still facing a trade-off between lighting fidelity and temporal consistency. Moving beyond relighting, a key step toward generative modeling of real-world…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Tianqi Liu , Zhaoxi Chen , Zihao Huang , Shaocong Xu , Saining Zhang , Chongjie Ye , Bohan Li , Zhiguo Cao , Wei Li , Hao Zhao , Ziwei Liu

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

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

We present StereoWorld, a camera-conditioned stereo world model that jointly learns appearance and binocular geometry for end-to-end stereo video generation.Unlike monocular RGB or RGBD approaches, StereoWorld operates exclusively within…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Yang-Tian Sun , Zehuan Huang , Yifan Niu , Lin Ma , Yan-Pei Cao , Yuewen Ma , Xiaojuan Qi

Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Shengqu Cai , Duygu Ceylan , Matheus Gadelha , Chun-Hao Paul Huang , Tuanfeng Yang Wang , Gordon Wetzstein

We present a dynamic reconstruction system that receives a casual monocular RGB video as input, and outputs a complete and persistent reconstruction of the scene. In other words, we reconstruct not only the the currently visible parts of…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Kirill Mazur , Marwan Taher , Andrew J. Davison

With the rapid development of 3D reconstruction technology, research in 4D reconstruction is also advancing, existing 4D reconstruction methods can generate high-quality 4D scenes. However, due to the challenges in acquiring multi-view…

Computer Vision and Pattern Recognition · Computer Science 2025-05-01 Ling Yang , Kaixin Zhu , Juanxi Tian , Bohan Zeng , Mingbao Lin , Hongjuan Pei , Wentao Zhang , Shuicheng Yan

Driving World Models (DWMs) have been developing rapidly with the advances of generative models. However, existing DWMs lack 3D scene understanding capabilities and can only generate content conditioned on input data, without the ability to…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Tianchen Deng , Xuefeng Chen , Yi Chen , Qu Chen , Yuyao Xu , Lijin Yang , Le Xu , Yu Zhang , Bo Zhang , Wuxiong Huang , Hesheng Wang

Humans excel at forecasting the future dynamics of a scene given just a single image. Video generation models that can mimic this ability are an essential component for intelligent systems. Recent approaches have improved temporal coherence…

Computer Vision and Pattern Recognition · Computer Science 2026-05-18 Melonie de Almeida , Daniela Ivanova , Tong Shi , John H. Williamson , Paul Henderson

World-model-based imagine-then-act becomes a promising paradigm for robotic manipulation, yet existing approaches typically support either purely image-based forecasting or reasoning over partial 3D geometry, limiting their ability to…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Jiaxu Wang , Yicheng Jiang , Tianlun He , Jingkai Sun , Qiang Zhang , Junhao He , Jiahang Cao , Zesen Gan , Mingyuan Sun , Qiming Shao , Xiangyu Yue

Recent techniques for text-to-4D generation synthesize dynamic 3D scenes using supervision from pre-trained text-to-video models. However, existing representations for motion, such as deformation models or time-dependent neural…

Computer Vision and Pattern Recognition · Computer Science 2024-10-16 Sherwin Bahmani , Xian Liu , Wang Yifan , Ivan Skorokhodov , Victor Rong , Ziwei Liu , Xihui Liu , Jeong Joon Park , Sergey Tulyakov , Gordon Wetzstein , Andrea Tagliasacchi , David B. Lindell

Automatically generating high-quality real world 3D scenes is of enormous interest for applications such as virtual reality and robotics simulation. Towards this goal, we introduce NeuralField-LDM, a generative model capable of synthesizing…

Computer Vision and Pattern Recognition · Computer Science 2023-04-20 Seung Wook Kim , Bradley Brown , Kangxue Yin , Karsten Kreis , Katja Schwarz , Daiqing Li , Robin Rombach , Antonio Torralba , Sanja Fidler

Interactive world models that simulate object dynamics are crucial for robotics, VR, and AR. However, it remains a significant challenge to learn physics-consistent dynamics models from limited real-world video data, especially for…

Computer Vision and Pattern Recognition · Computer Science 2025-10-27 Yu Yang , Zhilu Zhang , Xiang Zhang , Yihan Zeng , Hui Li , Wangmeng Zuo

Synthesizing photo-realistic visual observations from an ego vehicle's driving trajectory is a critical step towards scalable training of self-driving models. Reconstruction-based methods create 3D scenes from driving logs and synthesize…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Jiageng Mao , Boyi Li , Boris Ivanovic , Yuxiao Chen , Yan Wang , Yurong You , Chaowei Xiao , Danfei Xu , Marco Pavone , Yue Wang

Video world models have achieved remarkable success in simulating environmental dynamics in response to actions by users or agents. They are modeled as action-conditioned video generation models that take historical frames and current…

Computer Vision and Pattern Recognition · Computer Science 2026-04-22 Haoyu Wu , Jiwen Yu , Yingtian Zou , Xihui Liu

Recent advances in large language models (LLMs) have significantly improved language-driven 3D content generation, but most existing approaches still treat scene generation and user interaction as separate processes, limiting the…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Anh H. Vo , Sungyo Lee , Phil-Joong Kim , Soo-Mi Choi , Yong-Guk Kim

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

Cinematic video production requires control over scene-subject composition and camera movement, but live-action shooting remains costly due to the need for constructing physical sets. To address this, we introduce the task of cinematic…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Kaiyi Huang , Yukun Huang , Yu Li , Jianhong Bai , Xintao Wang , Zinan Lin , Xuefei Ning , Jiwen Yu , Pengfei Wan , Yu Wang , Xihui Liu

Driving world models serve as a pivotal technology for autonomous driving by simulating environmental dynamics. However, existing approaches predominantly focus on future scene generation, often overlooking comprehensive 3D scene…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Xin Zhou , Dingkang Liang , Xiwu Chen , Feiyang Tan , Dingyuan Zhang , Hengshuang Zhao , Xiang Bai