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Surface reconstruction has been widely studied in computer vision and graphics. However, existing surface reconstruction works struggle to recover accurate scene geometry when the input views are extremely sparse. To address this issue, we…

Graphics · Computer Science 2025-11-26 Hanzhi Chang , Ruijie Zhu , Wenjie Chang , Mulin Yu , Yanzhe Liang , Jiahao Lu , Zhuoyuan Li , Tianzhu Zhang

We propose DeMapGS, a structured Gaussian Splatting framework that jointly optimizes deformable surfaces and surface-attached 2D Gaussian splats. By anchoring splats to a deformable template mesh, our method overcomes topological…

Graphics · Computer Science 2025-12-12 Shuyi Zhou , Shengze Zhong , Kenshi Takayama , Takafumi Taketomi , Takeshi Oishi

Gaussian splatting has demonstrated excellent performance for view synthesis and scene reconstruction. The representation achieves photorealistic quality by optimizing the position, scale, color, and opacity of thousands to millions of 2D…

Computer Vision and Pattern Recognition · Computer Science 2025-02-27 Victor Rong , Jingxiang Chen , Sherwin Bahmani , Kiriakos N. Kutulakos , David B. Lindell

Reconstructing translucent objects from multi-view images is a difficult problem. Previously, researchers have used differentiable path tracing and the neural implicit field, which require relatively large computational costs. Recently,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Youwen Yuan , Xi Zhao

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

Recently, 2D Gaussian Splatting (2DGS) has demonstrated superior geometry reconstruction quality than the popular 3DGS by using 2D surfels to approximate thin surfaces. However, it falls short when dealing with glossy surfaces, resulting in…

Computer Vision and Pattern Recognition · Computer Science 2025-08-18 Yixin Yang , Yang Zhou , Hui Huang

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

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

We present 3D Surface Splatting (3DSS), the first differentiable surface splatting renderer for physically-based inverse rendering from multi-view images. Our central insight is that the surface separation problem at the heart of surface…

Graphics · Computer Science 2026-05-14 Mae Younes , Adnane Boukhayma

A well-designed vectorized representation is crucial for the learning systems natively based on 3D Gaussian Splatting. While 3DGS enables efficient and explicit 3D reconstruction, its parameter-based representation remains hard to learn as…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Yuelin Xin , Yuheng Liu , Xiaohui Xie , Xinke Li

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

3D Gaussian Splatting (3DGS) has recently emerged as a powerful paradigm for photorealistic view synthesis, representing scenes with spatially distributed Gaussian primitives. While highly effective for rendering, achieving accurate and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Wenzhi Guo , Bing Wang

We propose a material-aware optimization framework for high-fidelity mesh reconstruction from multi-view images based on 3D Gaussian Splatting, referred to as GS-2M. Previous works handle these tasks separately and struggle to reconstruct…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Dinh Minh Nguyen , Malte Avenhaus , Thomas Lindemeier

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

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

Recent advances in optimizing Gaussian Splatting for scene geometry have enabled efficient reconstruction of detailed surfaces from images. However, when input views are sparse, such optimization is prone to overfitting, leading to…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Meiying Gu , Jiawei Zhang , Jiahe Li , Xiaohan Yu , Haonan Luo , Jin Zheng , Xiao Bai

Reconstructing transparent surfaces is essential for tasks such as robotic manipulation in labs, yet it poses a significant challenge for 3D reconstruction techniques like 3D Gaussian Splatting (3DGS). These methods often encounter a…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Mingwei Li , Pu Pang , Hehe Fan , Hua Huang , Yi Yang

Touch and vision go hand in hand, mutually enhancing our ability to understand the world. From a research perspective, the problem of mixing touch and vision is underexplored and presents interesting challenges. To this end, we propose…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Mauro Comi , Alessio Tonioni , Max Yang , Jonathan Tremblay , Valts Blukis , Yijiong Lin , Nathan F. Lepora , Laurence Aitchison

Articulated objects, as prevalent entities in human life, their 3D representations play crucial roles across various applications. However, achieving both high-fidelity textured surface reconstruction and dynamic generation for articulated…

Computer Vision and Pattern Recognition · Computer Science 2025-11-24 Di Wu , Liu Liu , Zhou Linli , Anran Huang , Liangtu Song , Qiaojun Yu , Qi Wu , Cewu Lu

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