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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

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

3D Gaussian Splatting (3DGS) has shown impressive results in real-time novel view synthesis. However, it often struggles under sparse-view settings, producing undesirable artifacts such as floaters, inaccurate geometry, and overfitting due…

Graphics · Computer Science 2025-09-23 Gurutva Patle , Nilay Girgaonkar , Nagabhushan Somraj , Rajiv Soundararajan

Holistic 3D scene understanding, which jointly models geometry, appearance, and semantics, is crucial for applications like augmented reality and robotic interaction. Existing feed-forward 3D scene understanding methods (e.g., LSM) are…

Computer Vision and Pattern Recognition · Computer Science 2025-06-16 Qijing Li , Jingxiang Sun , Liang An , Zhaoqi Su , Hongwen Zhang , Yebin Liu

High-fidelity 3D Gaussian Splatting methods excel at capturing fine textures but often overlook model compactness, resulting in massive splat counts, bloated memory, long training, and complex post-processing. We present Micro-Splatting:…

Graphics · Computer Science 2025-09-03 Jee Won Lee , Hansol Lim , Sooyeun Yang , Jongseong Brad Choi

3D Gaussian Splatting (3DGS) has recently emerged as a promising 3D representation. Much research has been focused on reducing its storage requirements and memory footprint. However, the needs to compress and transmit the 3DGS…

Computer Vision and Pattern Recognition · Computer Science 2025-03-10 Yu-Ting Zhan , Cheng-Yuan Ho , Hebi Yang , Yi-Hsin Chen , Jui Chiu Chiang , Yu-Lun Liu , Wen-Hsiao Peng

3D Gaussian Splatting (3DGS) has demonstrated remarkable real-time performance in novel view synthesis, yet its effectiveness relies heavily on dense multi-view inputs with precisely known camera poses, which are rarely available in…

Computer Vision and Pattern Recognition · Computer Science 2025-08-22 Zongqi He , Hanmin Li , Kin-Chung Chan , Yushen Zuo , Hao Xie , Zhe Xiao , Jun Xiao , Kin-Man Lam

We introduce pixelSplat, a feed-forward model that learns to reconstruct 3D radiance fields parameterized by 3D Gaussian primitives from pairs of images. Our model features real-time and memory-efficient rendering for scalable training as…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 David Charatan , Sizhe Li , Andrea Tagliasacchi , Vincent Sitzmann

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

Recent works in volume rendering, \textit{e.g.} NeRF and 3D Gaussian Splatting (3DGS), significantly advance the rendering quality and efficiency with the help of the learned implicit neural radiance field or 3D Gaussians. Rendering on top…

Computer Vision and Pattern Recognition · Computer Science 2026-02-06 Xiaobiao Du , Yida Wang , Xin Yu

Recent approaches representing 3D objects and scenes using Gaussian splats show increased rendering speed across a variety of platforms and devices. While rendering such representations is indeed extremely efficient, storing and…

Graphics · Computer Science 2024-07-01 Junli Cao , Vidit Goel , Chaoyang Wang , Anil Kag , Ju Hu , Sergei Korolev , Chenfanfu Jiang , Sergey Tulyakov , Jian Ren

While 3D Gaussian Splatting has achieved remarkable success in photorealistic novel view synthesis, its pursuit of fast and high-fidelity 3D reconstruction has long been constrained by a trade-off between geometric accuracy and optimization…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Zhenhua Du , Zhen Tan , Haoyu Zhang , Dewen Hu , Shuaifeng Zhi , Peidong Liu

Intraoperative navigation relies heavily on precise 3D reconstruction to ensure accuracy and safety during surgical procedures. However, endoscopic scenarios present unique challenges, including sparse features and inconsistent lighting,…

Graphics · Computer Science 2025-07-17 Yuchao Zheng , Jianing Zhang , Guochen Ning , Hongen Liao

We present Splat-SAP, a feed-forward approach to render novel views of human-centered scenes from binocular cameras with large sparsity. Gaussian Splatting has shown its promising potential in rendering tasks, but it typically necessitates…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Boyao Zhou , Shunyuan Zheng , Zhanfeng Liao , Zihan Ma , Hanzhang Tu , Boning Liu , Yebin Liu

We present GauStudio, a novel modular framework for modeling 3D Gaussian Splatting (3DGS) to provide standardized, plug-and-play components for users to easily customize and implement a 3DGS pipeline. Supported by our framework, we propose…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Chongjie Ye , Yinyu Nie , Jiahao Chang , Yuantao Chen , Yihao Zhi , Xiaoguang Han

Recently, 3D Gaussian Splatting has emerged as a promising approach for modeling 3D scenes using mixtures of Gaussians. The predominant optimization method for these models relies on backpropagating gradients through a differentiable…

Computer Vision and Pattern Recognition · Computer Science 2025-09-24 Toon Van de Maele , Ozan Catal , Alexander Tschantz , Christopher L. Buckley , Tim Verbelen

3D Gaussian Splatting (3DGS) has emerged as a mainstream for novel view synthesis, leveraging continuous aggregations of Gaussian functions to model scene geometry. However, 3DGS suffers from substantial memory requirements to store the…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Yangming Zhang , Wenqi Jia , Wei Niu , Miao Yin

The recent introduction of 3D Gaussian Splatting (3DGS) has significantly advanced novel view synthesis. Several studies have further improved the rendering quality of 3DGS, yet they still exhibit noticeable visual discrepancies when…

Computer Vision and Pattern Recognition · Computer Science 2025-11-20 Junseo Koo , Jinseo Jeong , Gunhee Kim

Reconstructing and understanding 3D scenes from unposed sparse views in a feed-forward manner remains as a challenging task in 3D computer vision. Recent approaches use per-pixel 3D Gaussian Splatting for reconstruction, followed by a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-29 Honggyu An , Jaewoo Jung , Mungyeom Kim , Chaehyun Kim , Minkyeong Jeon , Jisang Han , Kazumi Fukuda , Takuya Narihira , Hyuna Ko , Junsu Kim , Sunghwan Hong , Yuki Mitsufuji , Seungryong Kim

We propose VideoRFSplat, a direct text-to-3D model leveraging a video generation model to generate realistic 3D Gaussian Splatting (3DGS) for unbounded real-world scenes. To generate diverse camera poses and unbounded spatial extent of…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Hyojun Go , Byeongjun Park , Hyelin Nam , Byung-Hoon Kim , Hyungjin Chung , Changick Kim