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While 3D Gaussian Splatting (3DGS) enables high-quality, real-time rendering for bounded scenes, its extension to large-scale urban environments gives rise to critical challenges in terms of geometric consistency, memory efficiency, and…

Computer Vision and Pattern Recognition · Computer Science 2026-02-23 Changbai Li , Haodong Zhu , Hanlin Chen , Xiuping Liang , Tongfei Chen , Shuwei Shao , Linlin Yang , Huobin Tan , Baochang Zhang

Accurate 3D reconstruction of dynamic surgical scenes from endoscopic video is essential for robotic-assisted surgery. While recent 3D Gaussian Splatting methods have shown promise in achieving high-quality reconstructions with fast…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Jialei Chen , Xin Zhang , Mobarakol Islam , Francisco Vasconcelos , Danail Stoyanov , Daniel S. Elson , Baoru Huang

Recently, 3D Gaussian Splatting (3DGS) has attracted widespread attention due to its high-quality rendering, and ultra-fast training and rendering speed. However, due to the unstructured and irregular nature of Gaussian point clouds, it is…

Computer Vision and Pattern Recognition · Computer Science 2025-01-13 Danpeng Chen , Hai Li , Weicai Ye , Yifan Wang , Weijian Xie , Shangjin Zhai , Nan Wang , Haomin Liu , Hujun Bao , Guofeng Zhang

High-fidelity three-dimensional (3D) reconstruction is essential for robotics and simulation. While Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) achieve impressive rendering quality, their reliance on time-consuming…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Xiong Jinlin , Li Can , Shen Jiawei , Qi Zhigang , Sun Lei , Zhao Dongyang

Efficiently synthesizing novel views from sparse inputs while maintaining accuracy remains a critical challenge in 3D reconstruction. While advanced techniques like radiance fields and 3D Gaussian Splatting achieve rendering quality and…

Computer Vision and Pattern Recognition · Computer Science 2025-01-22 Chenlu Zhan , Yufei Zhang , Yu Lin , Gaoang Wang , Hongwei Wang

We propose a method to enhance 3D Gaussian Splatting (3DGS)~\cite{Kerbl2023}, addressing challenges in initialization, optimization, and density control. Gaussian Splatting is an alternative for rendering realistic images while supporting…

Computer Vision and Pattern Recognition · Computer Science 2025-07-02 Xingjun Wang , Lianlei Shan

Generalizable 3D Gaussian Splatting reconstruction showcases advanced Image-to-3D content creation but requires substantial computational resources and large datasets, posing challenges to training models from scratch. Current methods…

Computer Vision and Pattern Recognition · Computer Science 2026-01-05 Xiufeng Huang , Ka Chun Cheung , Runmin Cong , Simon See , Renjie Wan

Recent advancements in 3D Gaussian Splatting (3DGS) have greatly influenced neural fields, as it enables high-fidelity rendering with impressive visual quality. However, 3DGS has difficulty accurately representing surfaces. In contrast,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Haofan Ren , Qingsong Yan , Ming Lu , Rongfeng Lu , Zunjie Zhu

Recently, the integration of the efficient feed-forward scheme into 3D Gaussian Splatting (3DGS) has been actively explored. However, most existing methods focus on sparse view reconstruction of small regions and cannot produce eligible…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Yunsong Wang , Tianxin Huang , Hanlin Chen , Gim Hee 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

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

3D Gaussian Splatting (3DGS) has recently revolutionized radiance field reconstruction, achieving high quality novel view synthesis and fast rendering speed without baking. However, 3DGS fails to accurately represent surfaces due to the…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Binbin Huang , Zehao Yu , Anpei Chen , Andreas Geiger , Shenghua Gao

Accurate geometric surface reconstruction, providing essential environmental information for navigation and manipulation tasks, is critical for enabling robotic self-exploration and interaction. Recently, 3D Gaussian Splatting (3DGS) has…

Computer Vision and Pattern Recognition · Computer Science 2025-07-17 Tengfei Wang , Xin Wang , Yongmao Hou , Zhaoning Zhang , Yiwei Xu , Zongqian Zhan

Reconstructing 3D scenes from sparse images remains a challenging task due to the difficulty of recovering accurate geometry and texture without optimization. Recent approaches leverage generalizable models to generate 3D scenes using 3D…

Computer Vision and Pattern Recognition · Computer Science 2026-02-04 Bing He , Jingnan Gao , Yunuo Chen , Ning Cao , Gang Chen , Zhengxue Cheng , Li Song , Wenjun Zhang

Recently, 3D Gaussian Splatting (3DGS) has demonstrated excellent ability in small-scale 3D surface reconstruction. However, extending 3DGS to large-scale scenes remains a significant challenge. To address this gap, we propose a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-09-24 YuanZheng Wu , Jin Liu , Shunping Ji

3D Gaussian Splatting (3DGS) leverages densely distributed Gaussian primitives for high-quality scene representation and reconstruction. While existing 3DGS methods perform well in scenes with minor view variation, large view changes from…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Chenhao Zhang , Yuanping Cao , Lei Zhang

3D Gaussian Splatting (3DGS) effectively synthesizes novel views through its flexible representation, yet fails to accurately reconstruct scene geometry. While modern variants like PGSR introduce additional losses to ensure proper depth and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Zhentao Huang , Di Wu , Zhenbang He , Minglun Gong

3D Gaussian Splatting (3DGS) achieves remarkable results in the field of surface reconstruction. However, when Gaussian normal vectors are aligned within the single-view projection plane, while the geometry appears reasonable in the current…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Bo Jia , Yanan Guo , Ying Chang , Benkui Zhang , Ying Xie , Kangning Du , Lin Cao

Recently, 3D Gaussian Splatting and its derivatives have achieved significant breakthroughs in large-scale scene reconstruction. However, how to efficiently and stably achieve high-quality geometric fidelity remains a core challenge. To…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Kehua Chen , Tianlu Mao , Xinzhu Ma , Hao Jiang , Zehao Li , Zihan Liu , Shuqin Gao , Honglong Zhao , Feng Dai , Yucheng Zhang , Zhaoqi Wang

Recent advances in radiance field reconstruction, such as 3D Gaussian Splatting (3DGS), have achieved high-quality novel view synthesis and fast rendering by representing scenes with compositions of Gaussian primitives. However, 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Jan Held , Renaud Vandeghen , Abdullah Hamdi , Adrien Deliege , Anthony Cioppa , Silvio Giancola , Andrea Vedaldi , Bernard Ghanem , Marc Van Droogenbroeck
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