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We introduce LivingWorld, an interactive framework for generating 4D worlds with environmental dynamics from a single image. While recent advances in 3D scene generation enable large-scale environment creation, most approaches focus…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Hyeongju Mun , In-Hwan Jin , Sohyeong Kim , Kyeongbo Kong

World models serve as essential building blocks toward Artificial General Intelligence (AGI), enabling intelligent agents to predict future states and plan actions by simulating complex physical interactions. However, existing interactive…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Junyi Chen , Haoyi Zhu , Xianglong He , Yifan Wang , Jianjun Zhou , Wenzheng Chang , Yang Zhou , Zizun Li , Zhoujie Fu , Jiangmiao Pang , Tong He

Emerging world models autoregressively generate video frames in response to actions, such as camera movements and text prompts, among other control signals. Due to limited temporal context window sizes, these models often struggle to…

Computer Vision and Pattern Recognition · Computer Science 2025-06-06 Tong Wu , Shuai Yang , Ryan Po , Yinghao Xu , Ziwei Liu , Dahua Lin , Gordon Wetzstein

Recent generative video world models aim to simulate visual environment evolution, allowing an observer to interactively explore the scene via camera control. However, they implicitly assume that the world only evolves within the observer's…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Zicheng Duan , Jiatong Xia , Zeyu Zhang , Wenbo Zhang , Gengze Zhou , Chenhui Gou , Yefei He , Feng Chen , Xinyu Zhang , Lingqiao Liu

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

Recent interactive video world model methods generate scene evolution conditioned on user instructions. Although they achieve impressive results, two key limitations remain. First, they exhibit motion drift in complex environments with…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Guangyuan Li , Bo Li , Jinwei Chen , Xiaobin Hu , Lei Zhao , Peng-Tao Jiang

Producing long, coherent video sequences with stable 3D structure remains a major challenge, particularly in streaming scenarios. Motivated by this, we introduce Endless World, a real-time framework for infinite, 3D-consistent video…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Ke Zhang , Yiqun Mei , Jiacong Xu , Vishal M. Patel

This paper presents WorldPlay, a streaming video diffusion model that enables real-time, interactive world modeling with long-term geometric consistency, resolving the trade-off between speed and memory that limits current methods.…

Computer Vision and Pattern Recognition · Computer Science 2025-12-17 Wenqiang Sun , Haiyu Zhang , Haoyuan Wang , Junta Wu , Zehan Wang , Zhenwei Wang , Yunhong Wang , Jun Zhang , Tengfei Wang , Chunchao Guo

World modeling has become a cornerstone in AI research, enabling agents to understand, represent, and predict the dynamic environments they inhabit. While prior work largely emphasizes generative methods for 2D image and video data, they…

Recent research has been increasingly focusing on developing 3D world models that simulate complex real-world scenarios. World models have found broad applications across various domains, including embodied AI, autonomous driving,…

Artificial Intelligence · Computer Science 2025-09-09 Yinglin Duan , Zhengxia Zou , Tongwei Gu , Wei Jia , Zhan Zhao , Luyi Xu , Xinzhu Liu , Yenan Lin , Hao Jiang , Kang Chen , Shuang Qiu

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

We introduce HY-World 2.0, a multi-modal world model framework that advances our prior project HY-World 1.0. HY-World 2.0 accommodates diverse input modalities, including text prompts, single-view images, multi-view images, and videos, and…

World models play a crucial role in understanding and predicting the dynamics of the world, which is essential for video generation. However, existing world models are confined to specific scenarios such as gaming or driving, limiting their…

Computer Vision and Pattern Recognition · Computer Science 2024-01-19 Xiaofeng Wang , Zheng Zhu , Guan Huang , Boyuan Wang , Xinze Chen , Jiwen Lu

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

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

Generative models have achieved success in producing apparently coherent 2D videos, but remain challenging in the physical world due to lack of 4D spatiotemporal scale. Typically, existing 4D generative models directly embed macro scale…

Computer Vision and Pattern Recognition · Computer Science 2026-05-11 Haonan Wang , Hanyu Zhou , Tao Gu , Luxin Yan

Video-based world models have recently garnered increasing attention for their ability to synthesize diverse and dynamic visual environments. In this paper, we focus on shared world modeling, where a model generates multiple videos from a…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Fan Wu , Jiacheng Wei , Ruibo Li , Yi Xu , Junyou Li , Deheng Ye , Guosheng Lin

In this paper, we explore the overlooked challenge of stability and temporal consistency in interactive video generation, which synthesizes dynamic and controllable video worlds through interactive behaviors such as camera movements and…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Ying Yang , Zhengyao Lv , Tianlin Pan , Haofan Wang , Binxin Yang , Hubery Yin , Chen Li , Ziwei Liu , Chenyang Si

The field of 4D world modeling - aiming to jointly capture spatial geometry and temporal dynamics - has witnessed remarkable progress in recent years, driven by advances in large-scale generative models and multimodal learning. However, the…

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
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