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Reconstructing objects and extracting high-quality surfaces play a vital role in the real world. Current 4D representations show the ability to render high-quality novel views for dynamic objects, but cannot reconstruct high-quality meshes…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Shuai Zhang , Guanjun Wu , Zhoufeng Xie , Xinggang Wang , Bin Feng , Wenyu Liu

We tackle the challenge of generating dynamic 4D scenes from monocular, multi-object videos with heavy occlusions, and introduce GenMOJO, a novel approach that integrates rendering-based deformable 3D Gaussian optimization with generative…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Wen-Hsuan Chu , Lei Ke , Jianmeng Liu , Mingxiao Huo , Pavel Tokmakov , Katerina Fragkiadaki

We present a new effective way for performance capture of deforming meshes with fine-scale time-varying surface detail from multi-view video. Our method builds up on coarse 4D surface reconstructions, as obtained with commonly used…

Computer Vision and Pattern Recognition · Computer Science 2016-02-08 Nadia Robertini , Edilson De Aguiar , Thomas Helten , Christian Theobalt

Single-view 3D human reconstruction has garnered significant attention in recent years. Despite numerous advancements, prior research has concentrated on reconstructing 3D models from clear, close-up images of individual subjects, often…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Yizheng Song , Yiyu Zhuang , Qipeng Xu , Haixiang Wang , Jiahe Zhu , Jing Tian , Siyu Zhu , Hao Zhu

Recently, 3D Gaussian Splatting (3DGS) has revolutionized radiance field reconstruction, manifesting efficient and high-fidelity novel view synthesis. However, accurately representing surfaces, especially in large and complex scenarios,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-05 Yang Liu , Chuanchen Luo , Zhongkai Mao , Junran Peng , Zhaoxiang Zhang

We introduce Mono4DGS-HDR, the first system for reconstructing renderable 4D high dynamic range (HDR) scenes from unposed monocular low dynamic range (LDR) videos captured with alternating exposures. To tackle such a challenging problem, we…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Jinfeng Liu , Lingtong Kong , Mi Zhou , Jinwen Chen , Dan Xu

We propose PoseGaussian, a pose-guided Gaussian Splatting framework for high-fidelity human novel view synthesis. Human body pose serves a dual purpose in our design: as a structural prior, it is fused with a color encoder to refine depth…

Computer Vision and Pattern Recognition · Computer Science 2026-02-06 Ju Shen , Chen Chen , Tam V. Nguyen , Vijayan K. Asari

Multi-view egocentric dynamic scene reconstruction holds significant research value for applications in holographic documentation of social interactions. However, existing reconstruction datasets focus on static multi-view or…

Computer Vision and Pattern Recognition · Computer Science 2025-12-15 Bate Li , Houqiang Zhong , Zhengxue Cheng , Qiang Hu , Qiang Wang , Li Song , Wenjun Zhang

3D Gaussian Splatting (3DGS) has emerged as a powerful technique for generating photorealistic renderings of a scene in real-time. However, the volumetric nature of 3DGS limits its ability to accurately capture surface geometry. To address…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Prajwal Gupta C. R. , Divyam Sheth , Jinjoo Ha , Mirela Ostrek , Justus Thies

Reconstructing and decomposing dynamic urban scenes is crucial for autonomous driving, urban planning, and scene editing. However, existing methods fail to perform instance-aware decomposition without manual annotations, which is crucial…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Yunxuan Mao , Rong Xiong , Yue Wang , Yiyi Liao

Existing NeRF-based methods for large scene reconstruction often have limitations in visual quality and rendering speed. While the recent 3D Gaussian Splatting works well on small-scale and object-centric scenes, scaling it up to large…

Computer Vision and Pattern Recognition · Computer Science 2024-02-28 Jiaqi Lin , Zhihao Li , Xiao Tang , Jianzhuang Liu , Shiyong Liu , Jiayue Liu , Yangdi Lu , Xiaofei Wu , Songcen Xu , Youliang Yan , Wenming Yang

The ability to extrapolate dynamic 3D scenes beyond the observed timeframe is fundamental to advancing physical world understanding and predictive modeling. Existing dynamic 3D reconstruction methods have achieved high-fidelity rendering of…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Jinsheng Quan , Qiaowei Miao , Yichao Xu , Zizhuo Lin , Ying Li , Wei Yang , Zhihui Li , Yawei Luo

Given a raw video sequence taken from a freely-moving camera, we study the problem of decomposing the observed 3D scene into a static background and a dynamic foreground containing the objects that move in the video sequence. This task is…

Computer Vision and Pattern Recognition · Computer Science 2021-10-20 Vadim Tschernezki , Diane Larlus , Andrea Vedaldi

Existing dynamic scene reconstruction methods based on Gaussian Splatting enable real-time rendering and generate realistic images. However, adjusting the camera's focal length or the distance between Gaussian primitives and the camera to…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Zilong Chen , Huan-ang Gao , Delin Qu , Haohan Chi , Hao Tang , Kai Zhang , Hao Zhao

Recent advancements in high-fidelity dynamic scene reconstruction have leveraged dynamic 3D Gaussians and 4D Gaussian Splatting for realistic scene representation. However, to make these methods viable for real-time applications such as…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Saqib Javed , Ahmad Jarrar Khan , Corentin Dumery , Chen Zhao , Mathieu Salzmann

High-fidelity visual reconstruction and novel-view synthesis are essential for realistic closed-loop evaluation in autonomous driving. While 4D Gaussian Splatting (4DGS) offers a promising balance of accuracy and efficiency, existing…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Haibao Yu , Kuntao Xiao , Jiahang Wang , Ruiyang Hao , Yuxin Huang , Guoran Hu , Haifang Qin , Bowen Jing , Yuntian Bo , Ping Luo

Low-level 3D representations, such as point clouds, meshes, NeRFs and 3D Gaussians, are commonly used for modeling 3D objects and scenes. However, cognitive studies indicate that human perception operates at higher levels and interprets 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Zhirui Gao , Renjiao Yi , Yuhang Huang , Wei Chen , Chenyang Zhu , Kai Xu

The modeling and manipulation of 3D scenes captured from the real world are pivotal in various applications, attracting growing research interest. While previous works on editing have achieved interesting results through manipulating 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-08-15 Guan Luo , Tian-Xing Xu , Ying-Tian Liu , Xiao-Xiong Fan , Fang-Lue Zhang , Song-Hai Zhang

Surgical reconstruction of dynamic tissues from endoscopic videos is a crucial technology in robot-assisted surgery. The development of Neural Radiance Fields (NeRFs) has greatly advanced deformable tissue reconstruction, achieving…

Computer Vision and Pattern Recognition · Computer Science 2025-11-03 Wenfeng Huang , Xiangyun Liao , Yinling Qian , Hao Liu , Yongming Yang , Wenjing Jia , Qiong Wang

Human-centric volumetric videos offer immersive free-viewpoint experiences, yet existing methods focus either on replaying general dynamic scenes or animating human avatars, limiting their ability to re-perform general dynamic scenes. In…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Yuheng Jiang , Zhehao Shen , Chengcheng Guo , Yu Hong , Zhuo Su , Yingliang Zhang , Marc Habermann , Lan Xu