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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

Recent successes in autoregressive (AR) generation models, such as the GPT series in natural language processing, have motivated efforts to replicate this success in visual tasks. Some works attempt to extend this approach to autonomous…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Xiaotao Hu , Wei Yin , Mingkai Jia , Junyuan Deng , Xiaoyang Guo , Qian Zhang , Xiaoxiao Long , Ping Tan

3D scene generation has garnered growing attention in recent years and has made significant progress. Generating 4D cities is more challenging than 3D scenes due to the presence of structurally complex, visually diverse objects like…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Haozhe Xie , Zhaoxi Chen , Fangzhou Hong , Ziwei Liu

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 advances in video diffusion transformers have enabled interactive gaming world models that allow users to explore generated environments over extended horizons. However, existing approaches struggle with precise action control and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Jisu Nam , Yicong Hong , Chun-Hao Paul Huang , Feng Liu , JoungBin Lee , Jiyoung Kim , Siyoon Jin , Yunsung Lee , Jaeyoon Jung , Suhwan Choi , Seungryong Kim , Yang Zhou

Closed-loop simulation is essential for advancing end-to-end autonomous driving systems. Contemporary sensor simulation methods, such as NeRF and 3DGS, rely predominantly on conditions closely aligned with training data distributions, which…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Guosheng Zhao , Chaojun Ni , Xiaofeng Wang , Zheng Zhu , Xueyang Zhang , Yida Wang , Guan Huang , Xinze Chen , Boyuan Wang , Youyi Zhang , Wenjun Mei , Xingang Wang

We present Playable Environments - a new representation for interactive video generation and manipulation in space and time. With a single image at inference time, our novel framework allows the user to move objects in 3D while generating a…

Computer Vision and Pattern Recognition · Computer Science 2022-03-17 Willi Menapace , Stéphane Lathuilière , Aliaksandr Siarohin , Christian Theobalt , Sergey Tulyakov , Vladislav Golyanik , Elisa Ricci

Generative world models are reshaping embodied AI, enabling agents to synthesize realistic 4D driving environments that look convincing but often fail physically or behaviorally. Despite rapid progress, the field still lacks a unified way…

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

High-quality 3D world models are pivotal for embodied intelligence and Artificial General Intelligence (AGI), underpinning applications such as AR/VR content creation and robotic navigation. Despite the established strong imaginative…

Computer Vision and Pattern Recognition · Computer Science 2025-11-03 Yixiang Dai , Fan Jiang , Chiyu Wang , Mu Xu , Yonggang Qi

We introduce Diff4Splat, a feed-forward method that synthesizes controllable and explicit 4D scenes from a single image. Our approach unifies the generative priors of video diffusion models with geometry and motion constraints learned from…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Panwang Pan , Chenguo Lin , Jingjing Zhao , Chenxin Li , Yuchen Lin , Haopeng Li , Honglei Yan , Kairun Wen , Yunlong Lin , Yixuan Yuan , Yadong Mu

Maintaining spatial world consistency over long horizons remains a central challenge for camera-controllable video generation. Existing memory-based approaches often condition generation on globally reconstructed 3D scenes by rendering…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Zun Wang , Han Lin , Jaehong Yoon , Jaemin Cho , Yue Zhang , Mohit Bansal

World simulators can provide safe and scalable environments for training Physical AI systems before real-world deployment. Large video generation models are emerging as a promising basis for such simulators because they can generate diverse…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Pu Zhao , Juyi Lin , Timothy Rupprecht , Arash Akbari , Chence Yang , Rahul Chowdhury , Elaheh Motamedi , Arman Akbari , Yumei He , Chen Wang , Geng Yuan , Weiwei Chen , Yanzhi Wang

We present DriveGen3D, a novel framework for generating high-quality and highly controllable dynamic 3D driving scenes that addresses critical limitations in existing methodologies. Current approaches to driving scene synthesis either…

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…

Despite the astonishing progress in generative AI, 4D dynamic object generation remains an open challenge. With limited high-quality training data and heavy computing requirements, the combination of hallucinating unseen geometry together…

Computer Vision and Pattern Recognition · Computer Science 2025-04-18 Lu Sang , Zehranaz Canfes , Dongliang Cao , Riccardo Marin , Florian Bernard , Daniel Cremers

In this paper we present a framework for the rendering of dynamic 3D virtual environments which can be integrated in the development of videogames. It includes methods to manage sounds and particle effects, paged static geometries, the…

Graphics · Computer Science 2013-06-06 Salvatore Catanese , Emilio Ferrara , Giacomo Fiumara , Francesco Pagano

Generating 4D scenes from a single-view video is inherently ill-posed: a single viewpoint lacks the information needed to recover a complete, dynamic scene with full coverage. Existing methods are typically limited to monocular videos,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Tingxi Chen , Ke Hao , Yabo Chen , Zhengxue Cheng , Rong Xie , Li Song , Haibin Huang , Chi Zhang , Xuelong Li

Recent advances in interactive video generations have demonstrated diffusion model's potential as world models by capturing complex physical dynamics and interactive behaviors. However, existing interactive world models depend on…