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We present a framework that enables fast reconstruction and real-time rendering of urban-scale scenes while maintaining robustness against appearance variations across multi-view captures. Our approach begins with scene partitioning for…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 Zhensheng Yuan , Haozhi Huang , Zhen Xiong , Di Wang , Guanghua Yang

Sparse-view scene reconstruction often faces significant challenges due to the constraints imposed by limited observational data. These limitations result in incomplete information, leading to suboptimal reconstructions using existing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Xiangyu Sun , Runnan Chen , Mingming Gong , Dong Xu , Tongliang Liu

Digitizing 3D static scenes and 4D dynamic events from multi-view images has long been a challenge in computer vision and graphics. Recently, 3D Gaussian Splatting (3DGS) has emerged as a practical and scalable reconstruction method,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-18 Marko Mihajlovic , Sergey Prokudin , Siyu Tang , Robert Maier , Federica Bogo , Tony Tung , Edmond Boyer

While 3D Gaussian Splatting (3DGS) excels in static scene modeling, its extension to dynamic scenes introduces significant challenges. Existing dynamic 3DGS methods suffer from either over-smoothing due to low-rank decomposition or feature…

Graphics · Computer Science 2025-08-08 Yifan Zhou , Beizhen Zhao , Pengcheng Wu , Hao Wang

Recent developments in 3D Gaussian Splatting have made significant advances in surface reconstruction. However, scaling these methods to large-scale scenes remains challenging due to high computational demands and the complex dynamic…

Graphics · Computer Science 2025-06-24 Shihan Chen , Zhaojin Li , Zeyu Chen , Qingsong Yan , Gaoyang Shen , Ran Duan

While the field of 3D scene reconstruction is dominated by NeRFs due to their photorealistic quality, 3D Gaussian Splatting (3DGS) has recently emerged, offering similar quality with real-time rendering speeds. However, both methods…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Jonas Kulhanek , Songyou Peng , Zuzana Kukelova , Marc Pollefeys , Torsten Sattler

3D Gaussian Splatting (3DGS) is a highly deployable real-time method for novel view synthesis. In practice, it requires a universal, consistent control mechanism that adjusts the trade-off between rendering quality and model compression…

Computer Vision and Pattern Recognition · Computer Science 2025-11-10 Fengdi Zhang , Yibao Sun , Hongkun Cao , Ruqi Huang

Understanding 3D scenes is pivotal for autonomous driving, robotics, and augmented reality. Recent semantic Gaussian Splatting approaches leverage large-scale 2D vision models to project 2D semantic features onto 3D scenes. However, they…

Computer Vision and Pattern Recognition · Computer Science 2025-10-22 Tianyu Huang , Runnan Chen , Dongting Hu , Fengming Huang , Mingming Gong , Tongliang Liu

3D Gaussian Splatting (3DGS) enables efficient training and fast novel view synthesis in static environments. To address challenges posed by transient objects, distractor-free 3DGS methods have emerged and shown promising results when dense…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Yi Gu , Zhaorui Wang , Jiahang Cao , Jiaxu Wang , Mingle Zhao , Dongjun Ye , Renjing Xu

3D Gaussian Splatting (3DGS) proposes an efficient solution for novel view synthesis. Its framework provides fast and high-fidelity rendering. Although less complex than other solutions such as Neural Radiance Fields (NeRF), there are still…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Stéphane Pateux , Matthieu Gendrin , Luce Morin , Théo Ladune , Xiaoran Jiang

Following the advent of NeRFs, 3D Gaussian Splatting (3D-GS) has paved the way to real-time neural rendering overcoming the computational burden of volumetric methods. Following the pioneering work of 3D-GS, several methods have attempted…

Computer Vision and Pattern Recognition · Computer Science 2024-05-01 Evangelos Ververas , Rolandos Alexandros Potamias , Jifei Song , Jiankang Deng , Stefanos Zafeiriou

Recent advances in 3D Gaussian Splatting (3DGS) enable real-time, high-fidelity novel view synthesis (NVS) with explicit 3D representations. However, performance degradation and instability remain significant under sparse-view conditions.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-10 Meixi Song , Xin Lin , Dizhe Zhang , Haodong Li , Xiangtai Li , Bo Du , Lu Qi

Three-dimensional Gaussian Splatting (3DGS) has recently emerged as an efficient representation for novel-view synthesis, achieving impressive visual quality. However, in scenes dominated by large and low-texture regions, common in indoor…

Computer Vision and Pattern Recognition · Computer Science 2025-10-29 Xirui Jin , Renbiao Jin , Boying Li , Danping Zou , Wenxian Yu

3D Gaussian Splatting (3DGS) enables efficient rendering, yet accurate surface reconstruction remains challenging due to unreliable geometric supervision. Existing approaches predominantly rely on depth-based reprojection to infer…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Mai Su , Qihan Yu , Zhongtao Wang , Yilong Li , Chengwei Pan , Yisong Chen , Guoping Wang , Fei Zhu

3D Gaussian Splatting (3DGS) has gained significant attention for its real-time, photo-realistic rendering in novel-view synthesis and 3D modeling. However, existing methods struggle with accurately modeling in-the-wild scenes affected by…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Chuanyu Fu , Guanying Chen , Yuqi Zhang , Kunbin Yao , Yuan Xiong , Chuan Huang , Shuguang Cui , Yasuyuki Matsushita , Xiaochun Cao

3D Gaussian Splatting (3DGS) has gained significant attention for 3D scene reconstruction, but still suffers from complex outdoor environments, especially under adverse weather. This is because 3DGS treats the artifacts caused by adverse…

Computer Vision and Pattern Recognition · Computer Science 2025-02-13 Chenghao Qian , Yuhu Guo , Wenjing Li , Gustav Markkula

Online reconstruction of dynamic scenes aims to learn from streaming multi-view inputs under low-latency constraints. The fast training and real-time rendering capabilities of 3D Gaussian Splatting have made on-the-fly reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Wonjoon Lee , Sungmin Woo , Donghyeong Kim , Jungho Lee , Sangheon Park , Sangyoun Lee

Recent advances in 3D Gaussian Splatting (3DGS) have enabled real-time, photorealistic scene reconstruction. However, conventional 3DGS frameworks typically rely on sparse point clouds derived from Structure-from-Motion (SfM), which…

Graphics · Computer Science 2026-03-25 Yan Fang , Jianfei Ge , Jiangjian Xiao

Dynamic scene rendering and reconstruction play a crucial role in computer vision and augmented reality. Recent methods based on 3D Gaussian Splatting (3DGS), have enabled accurate modeling of dynamic urban scenes, but for urban scenes they…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Siddharth Tourani , Jayaram Reddy , Akash Kumbar , Satyajit Tourani , Nishant Goyal , Madhava Krishna , N. Dinesh Reddy , Muhammad Haris Khan

Dynamic scene reconstruction has garnered significant attention in recent years due to its capabilities in high-quality and real-time rendering. Among various methodologies, constructing a 4D spatial-temporal representation, such as 4D-GS,…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Weiwei Cai , Weicai Ye , Peng Ye , Tong He , Tao Chen