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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

LiDAR-captured point clouds are often considered the gold standard in active 3D reconstruction. While their accuracy is exceptional in flat regions, the capturing is susceptible to miss small geometric structures and may fail with dark,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Svenja Strobel , Matthias Innmann , Bernhard Egger , Marc Stamminger , Linus Franke

Embodied intelligence requires precise reconstruction and rendering to simulate large-scale real-world data. Although 3D Gaussian Splatting (3DGS) has recently demonstrated high-quality results with real-time performance, it still faces…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Haodong Xiang , Xinghui Li , Kai Cheng , Xiansong Lai , Wanting Zhang , Zhichao Liao , Long Zeng , Xueping Liu

Recent advances in 3D Gaussian representations have significantly improved the quality and efficiency of image-based scene reconstruction. Their explicit nature facilitates real-time rendering and fast optimization, yet extracting accurate…

Reconstructing high-fidelity underwater scenes remains a challenging task due to light absorption, scattering, and limited visibility inherent in aquatic environments. This paper presents an enhanced Gaussian Splatting-based framework that…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Zhuodong Jiang , Haoran Wang , Guoxi Huang , Brett Seymour , Nantheera Anantrasirichai

In computer graphics and vision, recovering easily modifiable scene appearance from image data is crucial for applications such as content creation. We introduce a novel method that integrates 3D Gaussian Splatting with an implicit surface…

Computer Vision and Pattern Recognition · Computer Science 2025-02-11 Jakub Szymkowiak , Weronika Jakubowska , Dawid Malarz , Weronika Smolak-Dyżewska , Maciej Zięba , Przemyslaw Musialski , Wojtek Pałubicki , Przemysław Spurek

Recently, 3D Gaussian Splatting has dominated novel-view synthesis with its real-time rendering speed and state-of-the-art rendering quality. However, during the rendering process, the use of the Jacobian of the affine approximation of the…

Computer Vision and Pattern Recognition · Computer Science 2024-11-15 Han Qi , Tao Cai , Xiyue Han

We propose Quadratic Gaussian Splatting (QGS), a novel representation that replaces static primitives with deformable quadric surfaces (e.g., ellipse, paraboloids) to capture intricate geometry. Unlike prior works that rely on Euclidean…

Computer Vision and Pattern Recognition · Computer Science 2025-08-19 Ziyu Zhang , Binbin Huang , Hanqing Jiang , Liyang Zhou , Xiaojun Xiang , Shunhan Shen

We propose $S^3$LAM, a novel RGB-D SLAM system that leverages 2D surfel splatting to achieve highly accurate geometric representations for simultaneous tracking and mapping. Unlike existing 3DGS-based SLAM approaches that rely on 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Ruoyu Fan , Yuhui Wen , Jiajia Dai , Tao Zhang , Long Zeng , Yong-jin Liu

Reconstructing high-fidelity 3D hands from egocentric monocular videos remains a challenge due to the limitations in capturing high-resolution geometry, hand-object interactions, and complex objects on hands. Additionally, existing methods…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Haoyu Zhu , Yi Zhang , Lei Yao , Lap-pui Chau , Yi Wang

We introduce a framework for the recovery of points on a smooth surface in high-dimensional space, with application to dynamic imaging. We assume the surface to be the zero-level set of a bandlimited function. We show that the exponential…

Computer Vision and Pattern Recognition · Computer Science 2018-01-04 Sunrita Poddar , Mathews Jacob

Traditional volumetric fusion algorithms preserve the spatial structure of 3D scenes, which is beneficial for many tasks in computer vision and robotics. However, they often lack realism in terms of visualization. Emerging 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-11-18 Jiaxin Wei , Stefan Leutenegger

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

Recent advancements in 3D Gaussian Splatting (3DGS) have substantially improved novel view synthesis, enabling high-quality reconstruction and real-time rendering. However, blurring artifacts, such as floating primitives and…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Haodong Chen , Runnan Chen , Qiang Qu , Zhaoqing Wang , Tongliang Liu , Xiaoming Chen , Yuk Ying Chung

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

Spike cameras, as an innovative neuromorphic camera that captures scenes with the 0-1 bit stream at 40 kHz, are increasingly employed for the 3D reconstruction task via Neural Radiance Fields (NeRF) or 3D Gaussian Splatting (3DGS). Previous…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Kang Chen , Jiyuan Zhang , Zecheng Hao , Yajing Zheng , Tiejun Huang , Zhaofei Yu

3D surface reconstruction from point clouds is a key step in areas such as content creation, archaeology, digital cultural heritage, and engineering. Current approaches either try to optimize a non-data-driven surface representation to fit…

Computer Vision and Pattern Recognition · Computer Science 2024-02-09 Philipp Erler , Lizeth Fuentes , Pedro Hermosilla , Paul Guerrero , Renato Pajarola , Michael Wimmer

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

Neural rendering with Gaussian splatting has advanced novel view synthesis, and most methods reconstruct surfaces via post-hoc mesh extraction. However, existing methods suffer from two limitations: (i) inaccurate geometry in texture-less…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Yuhang Cao , Haojun Yan , Danya Yao

Planes are fundamental primitives of 3D sences, especially in man-made environments such as indoor spaces and urban streets. Representing these planes in a structured and parameterized format facilitates scene editing and physical…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Ruitong Gan , Junran Peng , Yang Liu , Chuanchen Luo , Qing Li , Zhaoxiang Zhang