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Recent advances in Gaussian Splatting based 3D scene representation have shown two major trends: semantics-oriented approaches that focus on high-level understanding but lack explicit 3D geometry modeling, and structure-oriented approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Yuhang Ming , Chenxin Fang , Xingyuan Yu , Fan Zhang , Weichen Dai , Wanzeng Kong , Guofeng Zhang

In this paper, we introduce Textured-GS, an innovative method for rendering Gaussian splatting that incorporates spatially defined color and opacity variations using Spherical Harmonics (SH). This approach enables each Gaussian to exhibit a…

Computer Vision and Pattern Recognition · Computer Science 2024-11-14 Zhentao Huang , Minglun Gong

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

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

Differentiable rendering techniques have recently shown promising results for free-viewpoint video synthesis of characters. However, such methods, either Gaussian Splatting or neural implicit rendering, typically necessitate per-subject…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Boyao Zhou , Shunyuan Zheng , Hanzhang Tu , Ruizhi Shao , Boning Liu , Shengping Zhang , Liqiang Nie , Yebin Liu

Transparent object manipulation remains a significant challenge in robotics due to the difficulty of acquiring accurate and dense depth measurements. Conventional depth sensors often fail with transparent objects, resulting in incomplete or…

Computer Vision and Pattern Recognition · Computer Science 2025-02-19 Jeongyun Kim , Jeongho Noh , Dong-Guw Lee , Ayoung Kim

3D Gaussian Splatting has achieved impressive performance in novel view synthesis with real-time rendering capabilities. However, reconstructing high-quality surfaces with fine details using 3D Gaussians remains a challenging task. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Jiepeng Wang , Yuan Liu , Peng Wang , Cheng Lin , Junhui Hou , Xin Li , Taku Komura , Wenping Wang

Feed-forward 3D reconstruction offers substantial runtime advantages over per-scene optimization, which remains slow at inference and often fragile under sparse views. However, existing feed-forward methods still have potential for further…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Tianyu Chen , Wei Xiang , Kang Han , Yu Lu , Di Wu , Gaowen Liu , Ramana Rao Kompella

3D Gaussian Splatting achieves high-fidelity novel view synthesis, but its application to online long-sequence scenarios is still limited. Existing methods either rely on slow per-scene optimization or fail to provide efficient incremental…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Guichen Huang , Ruoyu Wang , Xiangjun Gao , Che Sun , Yuwei Wu , Shenghua Gao , Yunde Jia

We propose a novel cross-spectral rendering framework based on 3D Gaussian Splatting (3DGS) that generates realistic and semantically meaningful splats from registered multi-view spectrum and segmentation maps. This extension enhances the…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Saptarshi Neil Sinha , Holger Graf , Michael Weinmann

Recent advances in Gaussian Splatting (GS) have demonstrated its effectiveness in photo-realistic rendering and 3D reconstruction. Among these, 2D Gaussian Splatting (2DGS) is particularly suitable for surface reconstruction due to its…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Qilin Zhang , Olaf Wysocki , Boris Jutzi

Feed-forward 3D Gaussian Splatting (3DGS) has emerged as a highly effective solution for novel view synthesis. Existing methods predominantly rely on a \emph{pixel-aligned} Gaussian prediction paradigm, where each 2D pixel is mapped to a 3D…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Weijie Wang , Yeqing Chen , Zeyu Zhang , Hengyu Liu , Haoxiao Wang , Zhiyuan Feng , Wenkang Qin , Feng Chen , Zheng Zhu , Donny Y. Chen , Bohan Zhuang

A major breakthrough in 3D reconstruction is the feedforward paradigm to generate pixel-wise 3D points or Gaussian primitives from sparse, unposed images. To further incorporate semantics while avoiding the significant memory and storage…

Computer Vision and Pattern Recognition · Computer Science 2025-10-13 Yu Sheng , Jiajun Deng , Xinran Zhang , Yu Zhang , Bei Hua , Yanyong Zhang , Jianmin Ji

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

As multimodal language models advance, their application to 3D scene understanding is a fast-growing frontier, driving the development of 3D Vision-Language Models (VLMs). Current methods show strong dependence on object detectors,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-02 Anna-Maria Halacheva , Jan-Nico Zaech , Xi Wang , Danda Pani Paudel , Luc Van Gool

Despite recent advancements in high-fidelity human reconstruction techniques, the requirements for densely captured images or time-consuming per-instance optimization significantly hinder their applications in broader scenarios. To tackle…

Computer Vision and Pattern Recognition · Computer Science 2024-10-31 Panwang Pan , Zhuo Su , Chenguo Lin , Zhen Fan , Yongjie Zhang , Zeming Li , Tingting Shen , Yadong Mu , Yebin Liu

Realistic scene reconstruction and view synthesis are essential for advancing autonomous driving systems by simulating safety-critical scenarios. 3D Gaussian Splatting excels in real-time rendering and static scene reconstructions but…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Mustafa Khan , Hamidreza Fazlali , Dhruv Sharma , Tongtong Cao , Dongfeng Bai , Yuan Ren , Bingbing Liu

We introduce Dr. Splat, a novel approach for open-vocabulary 3D scene understanding leveraging 3D Gaussian Splatting. Unlike existing language-embedded 3DGS methods, which rely on a rendering process, our method directly associates…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Kim Jun-Seong , GeonU Kim , Kim Yu-Ji , Yu-Chiang Frank Wang , Jaesung Choe , Tae-Hyun Oh

TL;DR: Gaussian Splatting is a widely adopted approach for 3D scene representation, offering efficient, high-quality reconstruction and rendering. A key reason for its success is the simplicity of representing scenes with sets of Gaussians,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Jiahuan Cheng , Jan-Nico Zaech , Luc Van Gool , Danda Pani Paudel

3D Gaussian Splatting (3DGS) has emerged as a powerful representation for neural scene reconstruction, offering high-quality novel view synthesis while maintaining computational efficiency. In this paper, we extend the capabilities of 3DGS…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Jens Piekenbrinck , Christian Schmidt , Alexander Hermans , Narunas Vaskevicius , Timm Linder , Bastian Leibe