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Gaussian Splatting (GS) is a popular approach for 3D reconstruction, mostly due to its ability to converge reasonably fast, faithfully represent the scene and render (novel) views in a fast fashion. However, it suffers from large storage…

Computer Vision and Pattern Recognition · Computer Science 2025-04-10 Anil Armagan , Albert Saà-Garriga , Bruno Manganelli , Kyuwon Kim , M. Kerim Yucel

3D Gaussian Splatting represents a breakthrough in the field of novel view synthesis. It establishes Gaussians as core rendering primitives for highly accurate real-world environment reconstruction. Recent advances have drastically…

Graphics · Computer Science 2025-06-25 Jonathan Haberl , Philipp Fleck , Clemens Arth

3D Gaussian Splatting (3DGS) has emerged as a powerful technique for novel view synthesis, demonstrating remarkable capability in high-fidelity scene reconstruction through its Gaussian primitive representations. However, the computational…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Chengbo Wang , Guozheng Ma , Yifei Xue , Yizhen Lao

3D Gaussian Splatting has recently achieved notable success in novel view synthesis for dynamic scenes and geometry reconstruction in static scenes. Building on these advancements, early methods have been developed for dynamic surface…

Computer Vision and Pattern Recognition · Computer Science 2024-11-12 Decai Chen , Brianne Oberson , Ingo Feldmann , Oliver Schreer , Anna Hilsmann , Peter Eisert

The problem of 3D reconstruction from posed images is undergoing a fundamental transformation, driven by continuous advances in 3D Gaussian Splatting (3DGS). By modeling scenes explicitly as collections of 3D Gaussians, 3DGS enables…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Vitor Pereira Matias , Daniel Perazzo , Vinicius Silva , Alberto Raposo , Luiz Velho , Afonso Paiva , Tiago Novello

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

In this paper, we propose UniGS, a unified map representation and differentiable framework for high-fidelity multimodal 3D reconstruction based on 3D Gaussian Splatting. Our framework integrates a CUDA-accelerated rasterization pipeline…

Computer Vision and Pattern Recognition · Computer Science 2025-11-14 Yusen Xie , Zhenmin Huang , Jianhao Jiao , Dimitrios Kanoulas , Jun Ma

3D Gaussian Splatting reconstructs scenes by starting from a sparse Structure-from-Motion initialization and refining under-reconstructed regions. This process is slow, as it requires multiple densification steps where Gaussians are…

Graphics · Computer Science 2026-02-13 Dmytro Kotovenko , Olga Grebenkova , Björn Ommer

Reconstructing urban street scenes is crucial due to its vital role in applications such as autonomous driving and urban planning. These scenes are characterized by long and narrow camera trajectories, occlusion, complex object…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Xiao Cui , Weicai Ye , Yifan Wang , Guofeng Zhang , Wengang Zhou , Houqiang Li

Recently, Gaussian Splatting (GS) has received a lot of attention in surface reconstruction. However, while 3D objects can be of complex and diverse shapes in the real world, existing GS-based methods only limitedly use a single type of…

Computer Vision and Pattern Recognition · Computer Science 2025-07-16 Haoxuan Qu , Yujun Cai , Hossein Rahmani , Ajay Kumar , Junsong Yuan , Jun Liu

Gaussian splatting (GS) for 3D reconstruction has become quite popular due to their fast training, inference speeds and high quality reconstruction. However, GS-based reconstructions generally consist of millions of Gaussians, which makes…

Computer Vision and Pattern Recognition · Computer Science 2025-01-27 Anil Armagan , Albert Saà-Garriga , Bruno Manganelli , Mateusz Nowak , Mehmet Kerim Yucel

3D Gaussian Splatting (3DGS) has garnered significant attention due to its superior scene representation fidelity and real-time rendering performance, especially for dynamic 3D scene reconstruction (\textit{i.e.}, 4D reconstruction).…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Henan Wang , Hanxin Zhu , Xinliang Gong , Tianyu He , Xin Li , Zhibo Chen

3D Gaussian splatting (3DGS) has demonstrated exceptional performance in image-based 3D reconstruction and real-time rendering. However, regions with complex textures require numerous Gaussians to capture significant color variations…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Binxiao Huang , Zhihao Li , Shiyong Liu , Xiao Tang , Jiajun Tang , Jiaqi Lin , Yuxin Cheng , Zhenyu Chen , Xiaofei Wu , Ngai Wong

3D Gaussian Splatting has demonstrated remarkable real-time rendering capabilities and superior visual quality in novel view synthesis for static scenes. Building upon these advantages, researchers have progressively extended 3D Gaussians…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Han Jiao , Jiakai Sun , Lei Zhao , Zhanjie Zhang , Wei Xing , Huaizhong Lin

We tackle the challenge of efficiently reconstructing 3D scenes with high detail on objects of interest. Existing 3D Gaussian Splatting (3DGS) methods allocate resources uniformly across the scene, limiting fine detail to Regions Of…

Graphics · Computer Science 2025-10-20 Quoc-Anh Bui , Gilles Rougeron , Géraldine Morin , Simone Gasparini

3D Gaussian Splatting has recently emerged as a highly promising technique for modeling of static 3D scenes. In contrast to Neural Radiance Fields, it utilizes efficient rasterization allowing for very fast rendering at high-quality.…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Wieland Morgenstern , Florian Barthel , Anna Hilsmann , Peter Eisert

3D Gaussian Splatting (3DGS) has emerged as a promising 3D reconstruction technique. The traditional 3DGS training pipeline follows three sequential steps: Gaussian densification, Gaussian projection, and color splatting. Despite its…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Junyi Wu , Jiaming Xu , Jinhao Li , Yongkang Zhou , Jiayi Pan , Xingyang Li , Guohao Dai

Accurate 3D reconstruction in degraded imaging conditions remains a key challenge in photogrammetry and neural rendering. In underwater environments, spatially varying visibility caused by scattering, attenuation, and sparse observations…

Computer Vision and Pattern Recognition · Computer Science 2026-04-23 Zhuodong Jiang , Haoran Wang , Guoxi Huang , Brett Seymour , Nantheera Anantrasirichai

We introduce ActiveGAMER, an active mapping system that utilizes 3D Gaussian Splatting (3DGS) to achieve high-quality, real-time scene mapping and exploration. Unlike traditional NeRF-based methods, which are computationally demanding and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-08 Liyan Chen , Huangying Zhan , Kevin Chen , Xiangyu Xu , Qingan Yan , Changjiang Cai , Yi Xu

Accurately reconstructing a 3D scene including explicit geometry information is both attractive and challenging. Geometry reconstruction can benefit from incorporating differentiable appearance models, such as Neural Radiance Fields and 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Ancheng Lin , Yusheng Xiang , Paul Kennedy , Jun Li