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Related papers: C4D: 4D Made from 3D through Dual Correspondences

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Monocular dynamic reconstruction is a challenging and long-standing vision problem due to the highly ill-posed nature of the task. Existing approaches depend on templates, are effective only in quasi-static scenes, or fail to model 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Qianqian Wang , Vickie Ye , Hang Gao , Weijia Zeng , Jake Austin , Zhengqi Li , Angjoo Kanazawa

Acquiring 3D geometry of real world objects has various applications in 3D digitization, such as navigation and content generation in virtual environments. Image remains one of the most popular media for such visual tasks due to its…

Computer Vision and Pattern Recognition · Computer Science 2017-01-26 Shuai Du , Youyi Zheng

This paper presents an approach for reconstruction of 4D temporally coherent models of complex dynamic scenes. No prior knowledge is required of scene structure or camera calibration allowing reconstruction from multiple moving cameras.…

Computer Vision and Pattern Recognition · Computer Science 2016-03-29 Armin Mustafa , Hansung Kim , Jean-Yves Guillemaut , Adrian Hilton

Dynamic 3D reconstruction and point tracking in videos are typically treated as separate tasks, despite their deep connection. We propose St4RTrack, a feed-forward framework that simultaneously reconstructs and tracks dynamic video content…

Computer Vision and Pattern Recognition · Computer Science 2025-04-18 Haiwen Feng , Junyi Zhang , Qianqian Wang , Yufei Ye , Pengcheng Yu , Michael J. Black , Trevor Darrell , Angjoo Kanazawa

Recovering a dynamic 3D scene from a long monocular video is crucial for dense geometry, camera motion, and temporal correspondence to remain consistent in a shared coordinate system. Existing methods face two key challenges: (1)…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Chenyi Xu , Yihao Wu , Liqi Yan , Chao Yang , Jianhui Zhang , Fangli Guan , Pan Li

Reconstructing dynamic 4D scenes from monocular videos is a fundamental yet challenging task. While recent 3D foundation models provide strong geometric priors, their performance significantly degrades in dynamic environments. This…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Ying Zang , Xuanyi Liu , Yidong Han , Deyi Ji , Chaotao Ding , Yuanqi Hu , Qi Zhu , Xuanfu Li , Jin Ma , Lingyun Sun , Tianrun Chen , Lanyun Zhu

This paper addresses the long-standing challenge of reconstructing 3D structures from videos with dynamic content. Current approaches to this problem were not designed to operate on casual videos recorded by standard cameras or require a…

Computer Vision and Pattern Recognition · Computer Science 2024-06-28 Yoni Kasten , Wuyue Lu , Haggai Maron

Reconstructing dense geometry for dynamic scenes from a monocular video is a critical yet challenging task. Recent memory-based methods enable efficient online reconstruction, but they fundamentally suffer from a Memory Demand Dilemma: The…

Computer Vision and Pattern Recognition · Computer Science 2025-08-13 Xudong Cai , Shuo Wang , Peng Wang , Yongcai Wang , Zhaoxin Fan , Wanting Li , Tianbao Zhang , Jianrong Tao , Yeying Jin , Deying Li

Accurate reconstruction and tracking of dynamic human faces from image sequences is challenging because non-rigid deformations, expression changes, and viewpoint variations occur simultaneously, creating significant ambiguity in geometry…

Computer Vision and Pattern Recognition · Computer Science 2026-04-22 Umut Kocasari , Simon Giebenhain , Richard Shaw , Matthias Nießner

We present To The Point (TTP), a method for reconstructing 3D objects from a single image using 2D to 3D correspondences learned from weak supervision. We recover a 3D shape from a 2D image by first regressing the 2D positions corresponding…

Computer Vision and Pattern Recognition · Computer Science 2021-06-11 Filippos Kokkinos , Iasonas Kokkinos

In this paper, we present Consistent4D, a novel approach for generating 4D dynamic objects from uncalibrated monocular videos. Uniquely, we cast the 360-degree dynamic object reconstruction as a 4D generation problem, eliminating the need…

Computer Vision and Pattern Recognition · Computer Science 2023-11-07 Yanqin Jiang , Li Zhang , Jin Gao , Weimin Hu , Yao Yao

We present Vista4D, a robust and flexible video reshooting framework that grounds the input video and target cameras in a 4D point cloud. Specifically, given an input video, our method re-synthesizes the scene with the same dynamics from a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Kuan Heng Lin , Zhizheng Liu , Pablo Salamanca , Yash Kant , Ryan Burgert , Yuancheng Xu , Koichi Namekata , Yiwei Zhao , Bolei Zhou , Micah Goldblum , Paul Debevec , Ning Yu

We introduce Geo4D, a method to repurpose video diffusion models for monocular 3D reconstruction of dynamic scenes. By leveraging the strong dynamic priors captured by large-scale pre-trained video models, Geo4D can be trained using only…

Computer Vision and Pattern Recognition · Computer Science 2025-08-20 Zeren Jiang , Chuanxia Zheng , Iro Laina , Diane Larlus , Andrea Vedaldi

Reconstructing 4D dynamic scenes from casually captured monocular videos is valuable but highly challenging, as each timestamp is observed from a single viewpoint. We introduce Vivid4D, a novel approach that enhances 4D monocular video…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Jiaxin Huang , Sheng Miao , BangBang Yang , Yuewen Ma , Yiyi Liao

This paper tackles the challenge of recovering 4D dynamic scenes from videos captured by as few as four portable cameras. Learning to model scene dynamics for temporally consistent novel-view rendering is a foundational task in computer…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Junsheng Zhou , Zhifan Yang , Liang Han , Wenyuan Zhang , Kanle Shi , Shenkun Xu , Yu-Shen Liu

The synthesis of spatiotemporally coherent 4D content presents fundamental challenges in computer vision, requiring simultaneous modeling of high-fidelity spatial representations and physically plausible temporal dynamics. Current…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Xiaoyan Liu , Kangrui Li , Yuehao Song , Jiaxin Liu

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

Learning to understand dynamic 3D scenes from imagery is crucial for applications ranging from robotics to scene reconstruction. Yet, unlike other problems where large-scale supervised training has enabled rapid progress, directly…

Computer Vision and Pattern Recognition · Computer Science 2025-05-01 Linyi Jin , Richard Tucker , Zhengqi Li , David Fouhey , Noah Snavely , Aleksander Holynski

Existing techniques for dynamic scene reconstruction from multiple wide-baseline cameras primarily focus on reconstruction in controlled environments, with fixed calibrated cameras and strong prior constraints. This paper introduces a…

Computer Vision and Pattern Recognition · Computer Science 2020-08-04 Armin Mustafa , Marco Volino , Hansung Kim , Jean-Yves Guillemaut , Adrian Hilton

We present Motion 3-to-4, a feed-forward framework for synthesising high-quality 4D dynamic objects from a single monocular video and an optional 3D reference mesh. While recent advances have significantly improved 2D, video, and 3D content…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Hongyuan Chen , Xingyu Chen , Youjia Zhang , Zexiang Xu , Anpei Chen
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