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We propose FlashWorld, a generative model that produces 3D scenes from a single image or text prompt in seconds, 10~100$\times$ faster than previous works while possessing superior rendering quality. Our approach shifts from the…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Xinyang Li , Tengfei Wang , Zixiao Gu , Shengchuan Zhang , Chunchao Guo , Liujuan Cao

We introduce RealPlay, a neural network-based real-world game engine that enables interactive video generation from user control signals. Unlike prior works focused on game-style visuals, RealPlay aims to produce photorealistic, temporally…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Wenqiang Sun , Fangyun Wei , Jinjing Zhao , Xi Chen , Zilong Chen , Hongyang Zhang , Jun Zhang , Yan Lu

We extend multimodal transformers to include 3D camera motion as a conditioning signal for the task of video generation. Generative video models are becoming increasingly powerful, thus focusing research efforts on methods of controlling…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Andrew Marmon , Grant Schindler , José Lezama , Dan Kondratyuk , Bryan Seybold , Irfan Essa

Recent advances in 3D content generation have amplified demand for dynamic models that are both visually realistic and physically consistent. However, state-of-the-art video diffusion models frequently produce implausible results such as…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Siwei Meng , Yawei Luo , Ping Liu

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

We present a novel method for generating geometrically realistic and consistent orbital videos from a single image of an object. Existing video generation works mostly rely on pixel-wise attention to enforce view consistency across frames.…

Computer Vision and Pattern Recognition · Computer Science 2026-04-15 Rong Wang , Ruyi Zha , Ziang Cheng , Jiayu Yang , Pulak Purkait , Hongdong Li

3D content creation from a single image is a long-standing yet highly desirable task. Recent advances introduce 2D diffusion priors, yielding reasonable results. However, existing methods are not hyper-realistic enough for post-generation…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Tong Wu , Zhibing Li , Shuai Yang , Pan Zhang , Xinggang Pan , Jiaqi Wang , Dahua Lin , Ziwei Liu

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

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

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

Video generation models have achieved remarkable progress in creating high-quality, photorealistic content. However, their ability to accurately simulate physical phenomena remains a critical and unresolved challenge. This paper presents…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Jing Gu , Xian Liu , Yu Zeng , Ashwin Nagarajan , Fangrui Zhu , Daniel Hong , Yue Fan , Qianqi Yan , Kaiwen Zhou , Ming-Yu Liu , Xin Eric Wang

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

Recent generative video models achieve impressive visual quality but remain constrained by limited physical consistency and controllability. Existing video generation methods provide minimal physical control, and single-image-to-3D…

Graphics · Computer Science 2026-05-21 Xin Zhang , Yabo Chen , Yijie Fang , Wanying Qu , Haibin Huang , Chi Zhang , Feng Xu , Xuelong Li

We present MagicMirror, a framework for generating identity-preserved videos with cinematic-level quality and dynamic motion. While recent advances in video diffusion models have shown impressive capabilities in text-to-video generation,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Yuechen Zhang , Yaoyang Liu , Bin Xia , Bohao Peng , Zexin Yan , Eric Lo , Jiaya Jia

Generative models trained on internet data have revolutionized how text, image, and video content can be created. Perhaps the next milestone for generative models is to simulate realistic experience in response to actions taken by humans,…

Artificial Intelligence · Computer Science 2024-09-27 Sherry Yang , Yilun Du , Kamyar Ghasemipour , Jonathan Tompson , Leslie Kaelbling , Dale Schuurmans , Pieter Abbeel

Generating temporally coherent high fidelity video is an important milestone in generative modeling research. We make progress towards this milestone by proposing a diffusion model for video generation that shows very promising initial…

Computer Vision and Pattern Recognition · Computer Science 2022-06-24 Jonathan Ho , Tim Salimans , Alexey Gritsenko , William Chan , Mohammad Norouzi , David J. Fleet

Diffusion models currently achieve state-of-the-art performance for both conditional and unconditional image generation. However, so far, image diffusion models do not support tasks required for 3D understanding, such as view-consistent 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-02-22 Titas Anciukevičius , Zexiang Xu , Matthew Fisher , Paul Henderson , Hakan Bilen , Niloy J. Mitra , Paul Guerrero

In this work, we tackle the problem of real-world fluid animation from a still image. The key of our system is a surface-based layered representation deriving from video decomposition, where the scene is decoupled into a surface fluid layer…

Computer Vision and Pattern Recognition · Computer Science 2022-04-26 Siming Fan , Jingtan Piao , Chen Qian , Kwan-Yee Lin , Hongsheng Li

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

Video generation models have emerged as high-fidelity models of the physical world, capable of synthesizing high-quality videos capturing fine-grained interactions between agents and their environments conditioned on multi-modal user…