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Related papers: Full-4D: Generating Full-Scope 4D Scenes from a Si…

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We propose a novel approach for 3D video synthesis that is able to represent multi-view video recordings of a dynamic real-world scene in a compact, yet expressive representation that enables high-quality view synthesis and motion…

Computer Vision and Pattern Recognition · Computer Science 2022-05-04 Tianye Li , Mira Slavcheva , Michael Zollhoefer , Simon Green , Christoph Lassner , Changil Kim , Tanner Schmidt , Steven Lovegrove , Michael Goesele , Richard Newcombe , Zhaoyang Lv

Despite recent advancements in neural 3D reconstruction, the dependence on dense multi-view captures restricts their broader applicability. Additionally, 3D scene generation is vital for advancing embodied AI and world models, which depend…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Yuxin Zhang , Ziyu Lu , Hongbo Duan , Keyu Fan , Pengting Luo , Peiyu Zhuang , Mengyu Yang , Houde Liu

Reconstructing dynamic fluids from sparse views is a long-standing and challenging problem, due to the severe lack of 3D information from insufficient view coverage. While several pioneering approaches have attempted to address this issue…

Graphics · Computer Science 2026-04-14 Chen Li , Shanshan Dong , Sheng Qiu , Jianmin Han , Yibo Zhao , Zan Gao , Taku Komura , Kemeng Huang

Automatic 3D generation has recently attracted widespread attention. Recent methods have greatly accelerated the generation speed, but usually produce less-detailed objects due to limited model capacity or 3D data. Motivated by recent…

Computer Vision and Pattern Recognition · Computer Science 2024-03-12 Zilong Chen , Yikai Wang , Feng Wang , Zhengyi Wang , Huaping Liu

Reconstructing 3D objects from a single image is an intriguing but challenging problem. One promising solution is to utilize multi-view (MV) 3D reconstruction to fuse generated MV images into consistent 3D objects. However, the generated…

Computer Vision and Pattern Recognition · Computer Science 2024-01-30 Yizheng Chen , Rengan Xie , Qi Ye , Sen Yang , Zixuan Xie , Tianxiao Chen , Rong Li , Yuchi Huo

How can one efficiently generate high-quality, wide-scope 3D scenes from arbitrary single images? Existing methods suffer several drawbacks, such as requiring multi-view data, time-consuming per-scene optimization, distorted geometry in…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Hanwen Liang , Junli Cao , Vidit Goel , Guocheng Qian , Sergei Korolev , Demetri Terzopoulos , Konstantinos N. Plataniotis , Sergey Tulyakov , Jian Ren

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

In recent years, the increasing demand for dynamic 3D assets in design and gaming applications has given rise to powerful generative pipelines capable of synthesizing high-quality 4D objects. Previous methods generally rely on score…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Qi Sun , Zhiyang Guo , Ziyu Wan , Jing Nathan Yan , Shengming Yin , Wengang Zhou , Jing Liao , Houqiang Li

Recent breakthroughs in text-to-4D generation rely on pre-trained text-to-image and text-to-video models to generate dynamic 3D scenes. However, current text-to-4D methods face a three-way tradeoff between the quality of scene appearance,…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Sherwin Bahmani , Ivan Skorokhodov , Victor Rong , Gordon Wetzstein , Leonidas Guibas , Peter Wonka , Sergey Tulyakov , Jeong Joon Park , Andrea Tagliasacchi , David B. Lindell

Generating multi-view human images from a single view is a complex and significant challenge. Although recent advancements in multi-view object generation have shown impressive results with diffusion models, novel view synthesis for humans…

Computer Vision and Pattern Recognition · Computer Science 2024-12-05 Yu Feng , Shunsi Zhang , Jian Shu , Hanfeng Zhao , Guoliang Pang , Chi Zhang , Hao Wang

Advances in 3D reconstruction have enabled high-quality 3D capture, but require a user to collect hundreds to thousands of images to create a 3D scene. We present CAT3D, a method for creating anything in 3D by simulating this real-world…

Computer Vision and Pattern Recognition · Computer Science 2024-05-17 Ruiqi Gao , Aleksander Holynski , Philipp Henzler , Arthur Brussee , Ricardo Martin-Brualla , Pratul Srinivasan , Jonathan T. Barron , Ben Poole

This paper aims to address the challenge of reconstructing long volumetric videos from multi-view RGB videos. Recent dynamic view synthesis methods leverage powerful 4D representations, like feature grids or point cloud sequences, to…

Computer Vision and Pattern Recognition · Computer Science 2024-12-13 Zhen Xu , Yinghao Xu , Zhiyuan Yu , Sida Peng , Jiaming Sun , Hujun Bao , Xiaowei Zhou

Novel-view synthesis techniques achieve impressive results for static scenes but struggle when faced with the inconsistencies inherent to casual capture settings: varying illumination, scene motion, and other unintended effects that are…

Synthesizing novel views from a single view image is a highly ill-posed problem. We discover an effective solution to reduce the learning ambiguity by expanding the single-view view synthesis problem to a multi-view setting. Specifically,…

Computer Vision and Pattern Recognition · Computer Science 2023-04-21 Yang Zhou , Hanjie Wu , Wenxi Liu , Zheng Xiong , Jing Qin , Shengfeng He

Recent advancements in diffusion models for 2D and 3D content creation have sparked a surge of interest in generating 4D content. However, the scarcity of 3D scene datasets constrains current methodologies to primarily object-centric…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Dejia Xu , Hanwen Liang , Neel P. Bhatt , Hezhen Hu , Hanxue Liang , Konstantinos N. Plataniotis , Zhangyang Wang

Recent advancements in dynamic 3D scene reconstruction have shown promising results, enabling high-fidelity 3D novel view synthesis with improved temporal consistency. Among these, 4D Gaussian Splatting (4DGS) has emerged as an appealing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Seungjun Oh , Younggeun Lee , Hyejin Jeon , Eunbyung Park

Recent advances in the diffusion models have significantly improved text-to-image generation. However, generating videos from text is a more challenging task than generating images from text, due to the much larger dataset and higher…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Taegyeong Lee , Soyeong Kwon , Taehwan Kim

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

In this paper, we study video synthesis with emphasis on simplifying the generation conditions. Most existing video synthesis models or datasets are designed to address complex motions of a single object, lacking the ability of…

Computer Vision and Pattern Recognition · Computer Science 2023-05-24 Yang Wu , Zhibin Liu , Hefeng Wu , Liang Lin

With the popularity of monocular videos generated by video sharing and live broadcasting applications, reconstructing and editing dynamic scenes in stationary monocular cameras has become a special but anticipated technology. In contrast to…

Computer Vision and Pattern Recognition · Computer Science 2024-02-02 Weixing Xie , Xiao Dong , Yong Yang , Qiqin Lin , Jingze Chen , Junfeng Yao , Xiaohu Guo