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Reconstructing dynamic 3D scenes from monocular video remains fundamentally challenging due to the need to jointly infer motion, structure, and appearance from limited observations. Existing dynamic scene reconstruction methods based on…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Jiahui Li , Shengeng Tang , Jingxuan He , Gang Huang , Zhangye Wang , Yantao Pan , Lechao Cheng

High-dynamic scene reconstruction aims to represent static background with rigid spatial features and dynamic objects with deformed continuous spatiotemporal features. Typically, existing methods adopt unified representation model (e.g.,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Hanyu Zhou , Haonan Wang , Haoyue Liu , Yuxing Duan , Luxin Yan , Gim Hee Lee

Dynamic scene reconstruction is essential in robotic minimally invasive surgery, providing crucial spatial information that enhances surgical precision and outcomes. However, existing methods struggle to address the complex, temporally…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Fengze Li , Jishuai He , Jieming Ma , Zhijing Wu

Reconstructing realistic underwater scenes from underwater video remains a meaningful yet challenging task in the multimedia domain. The inherent spatiotemporal degradations in underwater imaging, including caustics, flickering,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-28 Shaohua Liu , Ning Gao , Zuoya Gu , Hongkun Dou , Yue Deng , Hongjue Li

Dynamic and static components in scenes often exhibit distinct properties, yet most 4D reconstruction methods treat them indiscriminately, leading to suboptimal performance in both cases. This work introduces SDD-4DGS, the first framework…

Computer Vision and Pattern Recognition · Computer Science 2025-03-13 Dai Sun , Huhao Guan , Kun Zhang , Xike Xie , S. Kevin Zhou

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

This paper addresses the problem of dynamic scene surface reconstruction using Gaussian Splatting (GS), aiming to recover temporally consistent geometry. While existing GS-based dynamic surface reconstruction methods can yield superior…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Renjie Wu , Hongdong Li , Jose M. Alvarez , Miaomiao Liu

Reconstructing urban scenes is challenging due to their complex geometries and the presence of potentially dynamic objects. 3D Gaussian Splatting (3DGS)-based methods have shown strong performance, but existing approaches often incorporate…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Ziwen Li , Jiaxin Huang , Runnan Chen , Yunlong Che , Yandong Guo , Tongliang Liu , Fakhri Karray , Mingming Gong

Novel view synthesis has shown rapid progress recently, with methods capable of producing increasingly photorealistic results. 3D Gaussian Splatting has emerged as a promising method, producing high-quality renderings of scenes and enabling…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Richard Shaw , Michal Nazarczuk , Jifei Song , Arthur Moreau , Sibi Catley-Chandar , Helisa Dhamo , Eduardo Perez-Pellitero

Reconstructing dynamic 3D scenes from 2D images and generating diverse views over time is challenging due to scene complexity and temporal dynamics. Despite advancements in neural implicit models, limitations persist: (i) Inadequate Scene…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 Zeyu Yang , Hongye Yang , Zijie Pan , Li Zhang

Real-time rendering of dynamic scenes with view-dependent effects remains a fundamental challenge in computer graphics. While recent advances in Gaussian Splatting have shown promising results separately handling dynamic scenes (4DGS) and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Zhongpai Gao , Benjamin Planche , Meng Zheng , Anwesa Choudhuri , Terrence Chen , Ziyan Wu

3D Gaussian Splatting (3DGS) has shown remarkable potential for static scene reconstruction, and recent advancements have extended its application to dynamic scenes. However, the quality of reconstructions depends heavily on high-quality…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Yiren Lu , Yunlai Zhou , Disheng Liu , Tuo Liang , Yu Yin

Maintaining consistent 3D scene representations over time is a significant challenge in computer vision. Updating 3D scenes from sparse-view observations is crucial for various real-world applications, including urban planning, disaster…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Zeyuan An , Yanghang Xiao , Zhiying Leng , Frederick W. B. Li , Xiaohui Liang

3D Gaussian Splatting, known for enabling high-quality static scene reconstruction with fast rendering, is increasingly being applied to multi-view dynamic scene reconstruction. A common strategy involves learning a deformation field to…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Han Jiao , Jiakai Sun , Yexing Xu , Lei Zhao , Wei Xing , Huaizhong Lin

3D occupancy prediction is critical for comprehensive scene understanding in vision-centric autonomous driving. Recent advances have explored utilizing 3D semantic Gaussians to model occupancy while reducing computational overhead, but they…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Xiaoyang Yan , Muleilan Pei , Shaojie Shen

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

Previous surface reconstruction methods either suffer from low geometric accuracy or lengthy training times when dealing with real-world complex dynamic scenes involving multi-person activities, and human-object interactions. To tackle the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Shuo Wang , Binbin Huang , Ruoyu Wang , Shenghua Gao

Implicit neural representation has paved the way for new approaches to dynamic scene reconstruction and rendering. Nonetheless, cutting-edge dynamic neural rendering methods rely heavily on these implicit representations, which frequently…

Computer Vision and Pattern Recognition · Computer Science 2023-11-22 Ziyi Yang , Xinyu Gao , Wen Zhou , Shaohui Jiao , Yuqing Zhang , Xiaogang Jin

3D Gaussian Splatting (3DGS) has emerged as a powerful explicit representation enabling real-time, high-fidelity 3D reconstruction and novel view synthesis. However, its practical use is hindered by the massive memory and computational…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Seokhyun Youn , Soohyun Lee , Geonho Kim , Weeyoung Kwon , Sung-Ho Bae , Jihyong Oh

Deformable 3D Gaussian Splatting (3D-GS) is limited by missing intermediate motion information due to the low temporal resolution of RGB cameras. To address this, we introduce the first approach combining event cameras, which capture…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Wenhao Xu , Wenming Weng , Yueyi Zhang , Ruikang Xu , Zhiwei Xiong
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