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Related papers: Video Generation Models as World Models: Efficient…

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Motion control is crucial for generating expressive and compelling video content; however, most existing video generation models rely mainly on text prompts for control, which struggle to capture the nuances of dynamic actions and temporal…

Video world models have shown immense promise for interactive simulation and entertainment, but current systems still struggle with two important aspects of interactivity: user control over the environment for reproducible, editable…

Artificial Intelligence · Computer Science 2026-04-01 Ryan Po , David Junhao Zhang , Amir Hertz , Gordon Wetzstein , Neal Wadhwa , Nataniel Ruiz

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…

360{\deg} videos have emerged as a promising medium to represent our dynamic visual world. Compared to the "tunnel vision" of standard cameras, their borderless field of view offers a more complete perspective of our surroundings. While…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Rundong Luo , Matthew Wallingford , Ali Farhadi , Noah Snavely , Wei-Chiu Ma

Video generation models have shown strong potential as world models for autonomous driving simulation. However, existing approaches are primarily trained on real-world driving datasets, which mostly contain natural and safe driving…

Computer Vision and Pattern Recognition · Computer Science 2026-04-02 Jiawei Zhou , Zhenxin Zhu , Lingyi Du , Linye Lyu , Lijun Zhou , Zhanqian Wu , Hongcheng Luo , Zhuotao Tian , Bing Wang , Guang Chen , Hangjun Ye , Haiyang Sun , Yu Li

The generation of high-quality 3D environments is crucial for industries such as gaming, virtual reality, and cinema, yet remains resource-intensive due to the reliance on manual processes. This study performs a systematic review of…

Graphics · Computer Science 2025-06-09 Miguel Silva , Alexandre Valle de Carvalho

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

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

Recent developments in generative models and large-scale datasets have substantially advanced 3D world generation, facilitating a broad range of domains including spatial intelligence, embodied intelligence, and autonomous driving. While…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Hanxin Zhu , Cong Wang , Peiyan Tu , Jiayi Luo , Tianyu He , Xin Jin , Zhibo Chen

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

Real-time generative game engines represent a paradigm shift in interactive simulation, promising to replace traditional graphics pipelines with neural world models. However, existing approaches are fundamentally constrained by the ``Memory…

Artificial Intelligence · Computer Science 2026-02-03 Wei Zeng , Xuchen Li , Ruili Feng , Zhen Liu , Fengwei An , Jian Zhao

We address the problem of generating long-horizon videos for robotic manipulation tasks. Text-to-video diffusion models have made significant progress in photorealism, language understanding, and motion generation but struggle with…

Computer Vision and Pattern Recognition · Computer Science 2025-06-30 Liudi Yang , Yang Bai , George Eskandar , Fengyi Shen , Mohammad Altillawi , Dong Chen , Soumajit Majumder , Ziyuan Liu , Gitta Kutyniok , Abhinav Valada

We introduce a class of causal video understanding models that aims to improve efficiency of video processing by maximising throughput, minimising latency, and reducing the number of clock cycles. Leveraging operation pipelining and…

Computer Vision and Pattern Recognition · Computer Science 2018-09-06 Joao Carreira , Viorica Patraucean , Laurent Mazare , Andrew Zisserman , Simon Osindero

Videos can be created by first outlining a global view of the scene and then adding local details. Inspired by this idea we propose a cascaded model for video generation which follows a coarse to fine approach. First our model generates a…

Computer Vision and Pattern Recognition · Computer Science 2022-06-03 Lluis Castrejon , Nicolas Ballas , Aaron Courville

Diffusion and flow matching models have unlocked unprecedented capabilities for creative content creation, such as interactive image and streaming video generation. The growing demand for higher resolutions, frame rates, and context…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Brian Chao , Lior Yariv , Howard Xiao , Gordon Wetzstein

Video generative models can be regarded as world simulators due to their ability to capture dynamic, continuous changes inherent in real-world environments. These models integrate high-dimensional information across visual, temporal,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Hengyuan Cao , Yutong Feng , Biao Gong , Yijing Tian , Yunhong Lu , Chuang Liu , Bin Wang

Video generation models hold substantial potential in areas such as filmmaking. However, current video diffusion models need high computational costs and produce suboptimal results due to extreme complexity of video generation task. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-12-30 Wenhao Li , Yichao Cao , Xiu Su , Xi Lin , Shan You , Mingkai Zheng , Yi Chen , Chang Xu

Recent advancements in video generation have enabled the development of ``world models'' capable of simulating potential futures for robotics and planning. However, specifying precise goals for these models remains a challenge; text…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Nate Gillman , Yinghua Zhou , Zitian Tang , Evan Luo , Arjan Chakravarthy , Daksh Aggarwal , Michael Freeman , Charles Herrmann , Chen Sun

The recent advent of powerful video generation models, such as Hunyuan, WanX, Veo3, and Kling, has inaugurated a new era in the field. However, the practical deployment of these models is severely impeded by their substantial computational…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Shitong Shao , Yufei Gu , Zeke Xie

Image and video synthesis are closely related areas aiming at generating content from noise. While rapid progress has been demonstrated in improving image-based models to handle large resolutions, high-quality renderings, and wide…

Computer Vision and Pattern Recognition · Computer Science 2021-05-03 Yu Tian , Jian Ren , Menglei Chai , Kyle Olszewski , Xi Peng , Dimitris N. Metaxas , Sergey Tulyakov