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In this work, we propose a novel method to supervise 3D Gaussian Splatting (3DGS) scenes using optical tactile sensors. Optical tactile sensors have become widespread in their use in robotics for manipulation and object representation;…

Robotics · Computer Science 2024-08-19 Aiden Swann , Matthew Strong , Won Kyung Do , Gadiel Sznaier Camps , Mac Schwager , Monroe Kennedy

Tissue deformation poses a key challenge for accurate surgical scene reconstruction. Despite yielding high reconstruction quality, existing methods suffer from slow rendering speeds and long training times, limiting their intraoperative…

Computer Vision and Pattern Recognition · Computer Science 2024-05-31 Shuojue Yang , Qian Li , Daiyun Shen , Bingchen Gong , Qi Dou , Yueming Jin

Reconstructing deformable endoscopic tissues is crucial for achieving robot-assisted surgery. However, 3D Gaussian Splatting-based approaches encounter challenges in achieving consistent tissue surface reconstruction, while existing…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Yangsen Chen , Hao Wang

We present GSEdit, a pipeline for text-guided 3D object editing based on Gaussian Splatting models. Our method enables the editing of the style and appearance of 3D objects without altering their main details, all in a matter of minutes on…

Computer Vision and Pattern Recognition · Computer Science 2024-05-22 Francesco Palandra , Andrea Sanchietti , Daniele Baieri , Emanuele Rodolà

Recent advancements in 3D Gaussian Splatting(3DGS) have significantly improved semantic scene understanding, enabling natural language queries to localize objects within a scene. However, existing methods primarily focus on embedding…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Xihan Wang , Dianyi Yang , Yu Gao , Yufeng Yue , Yi Yang , Mengyin Fu

3D Gaussian Splatting (3D-GS) has emerged as a significant advancement in the field of Computer Graphics, offering explicit scene representation and novel view synthesis without the reliance on neural networks, such as Neural Radiance…

Computer Vision and Pattern Recognition · Computer Science 2024-07-11 Ben Fei , Jingyi Xu , Rui Zhang , Qingyuan Zhou , Weidong Yang , Ying He

Dynamic scene reconstruction poses a persistent challenge in 3D vision. Deformable 3D Gaussian Splatting has emerged as an effective method for this task, offering real-time rendering and high visual fidelity. This approach decomposes a…

Computer Vision and Pattern Recognition · Computer Science 2025-10-22 Bing He , Yunuo Chen , Guo Lu , Qi Wang , Qunshan Gu , Rong Xie , Li Song , Wenjun Zhang

This paper investigates an open research challenge of reconstructing high-quality, large 3D open scenes from images. It is observed existing methods have various limitations, such as requiring precise camera poses for input and dense…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Chong Cheng , Gaochao Song , Yiyang Yao , Qinzheng Zhou , Gangjian Zhang , Hao Wang

Physics simulation is paramount for modeling and utilizing 3D scenes in various real-world applications. However, integrating with state-of-the-art 3D scene rendering techniques such as Gaussian Splatting (GS) remains challenging. Existing…

Computer Vision and Pattern Recognition · Computer Science 2025-11-03 Piotr Borycki , Weronika Smolak , Joanna Waczyńska , Marcin Mazur , Sławomir Tadeja , Przemysław Spurek

3D Gaussian Splatting (3DGS) enables high-fidelity real-time rendering, a key requirement for immersive applications. However, the extension of 3DGS to dynamic scenes remains limitations on the substantial data volume of dense Gaussians and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-01 Jiayu Yang , Weijian Su , Songqian Zhang , Yuqi Han , Jinli Suo , Qiang Zhang

3D Gaussian Splatting (3DGS) has emerged as a powerful technique for real-time, high-resolution novel view synthesis. By representing scenes as a mixture of Gaussian primitives, 3DGS leverages GPU rasterization pipelines for efficient…

Computer Vision and Pattern Recognition · Computer Science 2025-05-12 Peihao Wang , Yuehao Wang , Dilin Wang , Sreyas Mohan , Zhiwen Fan , Lemeng Wu , Ruisi Cai , Yu-Ying Yeh , Zhangyang Wang , Qiang Liu , Rakesh Ranjan

Neural rendering methods have significantly advanced photo-realistic 3D scene rendering in various academic and industrial applications. The recent 3D Gaussian Splatting method has achieved the state-of-the-art rendering quality and speed…

Computer Vision and Pattern Recognition · Computer Science 2023-12-04 Tao Lu , Mulin Yu , Linning Xu , Yuanbo Xiangli , Limin Wang , Dahua Lin , Bo Dai

3D Gaussian Splatting (3DGS) has recently emerged as a pioneering approach in explicit scene rendering and computer graphics. Unlike traditional neural radiance field (NeRF) methods, which typically rely on implicit, coordinate-based models…

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

3D Gaussian Splatting has emerged as an alternative 3D representation for novel view synthesis, benefiting from its high-quality rendering results and real-time rendering speed. However, the 3D Gaussians learned by 3D-GS have ambiguous…

Computer Vision and Pattern Recognition · Computer Science 2025-01-22 Xu Hu , Yuxi Wang , Lue Fan , Chuanchen Luo , Junsong Fan , Zhen Lei , Qing Li , Junran Peng , Zhaoxiang Zhang

Articulated object manipulation remains a critical challenge in robotics due to the complex kinematic constraints and the limited physical reasoning of existing methods. In this work, we introduce ArtGS, a novel framework that extends 3D…

Robotics · Computer Science 2025-07-04 Qiaojun Yu , Xibin Yuan , Yu jiang , Junting Chen , Dongzhe Zheng , Ce Hao , Yang You , Yixing Chen , Yao Mu , Liu Liu , Cewu Lu

Deformable Gaussian Splatting (GS) accomplishes photorealistic dynamic 3-D reconstruction from dense multi-view video (MVV) by learning to deform a canonical GS representation. However, in filmmaking, tight budgets can result in sparse…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Adrian Azzarelli , Nantheera Anantrasirichai , David R Bull

Sketch-based shape modeling aims to bridge the gap between 2D drawing and 3D modeling by providing an intuitive and accessible approach to create 3D shapes from 2D sketches. However, existing methods still suffer from limitations in…

Graphics · Computer Science 2023-09-13 Jie Zhou , Zhongjin Luo , Qian Yu , Xiaoguang Han , Hongbo Fu

Gaussian splatting has emerged as a powerful tool for high-fidelity reconstruction of dynamic scenes. However, existing methods primarily rely on implicit motion representations, such as encoding motions into neural networks or per-Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Xinyu Zhang , Haonan Chang , Yuhan Liu , Abdeslam Boularias

A photorealistic and controllable 3D caricaturization framework for faces is introduced. We start with an intrinsic Gaussian curvature-based surface exaggeration technique, which, when coupled with texture, tends to produce over-smoothed…

Graphics · Computer Science 2026-01-08 Eldad Matmon , Amit Bracha , Noam Rotstein , Ron Kimmel