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3D Gaussian Splatting (3DGS) achieves high-fidelity rendering with fast real-time performance, but existing methods rely on offline training after full Structure-from-Motion (SfM) processing. In contrast, this work introduces Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-07-31 Yiwei Xu , Yifei Yu , Wentian Gan , Tengfei Wang , Zongqian Zhan , Hao Cheng , Xin Wang

In the domain of 3D scene representation, 3D Gaussian Splatting (3DGS) has emerged as a pivotal technology. However, its application to large-scale, high-resolution scenes (exceeding 4k$\times$4k pixels) is hindered by the excessive…

Computer Vision and Pattern Recognition · Computer Science 2024-04-22 Wenkai Liu , Tao Guan , Bin Zhu , Lili Ju , Zikai Song , Dan Li , Yuesong Wang , Wei Yang

Over the past year, 3D Gaussian Splatting (3DGS) has received significant attention for its ability to represent 3D scenes in a perceptually accurate manner. However, it can require a substantial amount of storage since each splat's…

Computer Vision and Pattern Recognition · Computer Science 2025-04-11 Brent Zoomers , Maarten Wijnants , Ivan Molenaers , Joni Vanherck , Jeroen Put , Lode Jorissen , Nick Michiels

3D Gaussian Splatting (3DGS) is a state-of-art technique to model real-world scenes with high quality and real-time rendering. Typically, a higher quality representation can be achieved by using a large number of 3D Gaussians. However,…

Recent advances in real-time neural rendering using point-based techniques have enabled broader adoption of 3D representations. However, foundational approaches like 3D Gaussian Splatting impose substantial storage overhead, as…

Computer Vision and Pattern Recognition · Computer Science 2024-11-13 Zhiwen Fan , Kevin Wang , Kairun Wen , Zehao Zhu , Dejia Xu , Zhangyang Wang

3D Gaussian Splatting enables high-quality real-time rendering but often produces millions of splats, resulting in excessive storage and computational overhead. We propose a novel lossy compression method based on learnable confidence…

Graphics · Computer Science 2025-07-01 AmirHossein Naghi Razlighi , Elaheh Badali Golezani , Shohreh Kasaei

3D Gaussian splatting (3DGS) has recently emerged as an alternative representation that leverages a 3D Gaussian-based representation and introduces an approximated volumetric rendering, achieving very fast rendering speed and promising…

Computer Vision and Pattern Recognition · Computer Science 2024-08-08 Joo Chan Lee , Daniel Rho , Xiangyu Sun , Jong Hwan Ko , Eunbyung Park

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…

3D Gaussian Splatting (3DGS) has demonstrated remarkable effectiveness in 3D reconstruction, achieving high-quality results with real-time radiance field rendering. However, a key challenge is the substantial storage cost: reconstructing a…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Haishan Wang , Mohammad Hassan Vali , Arno Solin

3D Gaussian Splatting is a recognized method for 3D scene representation, known for its high rendering quality and speed. However, its substantial data requirements present challenges for practical applications. In this paper, we introduce…

Computer Vision and Pattern Recognition · Computer Science 2025-01-08 Soonbin Lee , Fangwen Shu , Yago Sanchez , Thomas Schierl , Cornelius Hellge

3D Gaussian Splatting (3DGS) achieves high-quality novel view synthesis with real-time rendering, but its storage cost remains prohibitive for practical deployment. Existing post-training compression methods still rely on many coupled…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Shuzhao Xie , Junchen Ge , Weixiang Zhang , Jiahang Liu , Chen Tang , Yunpeng Bai , Shijia Ge , Jingyan Jiang , Yuzhi Huang , Fengnian Yang , Cong Zhang , Xiaoyi Fan , Zhi Wang

3D Gaussian Splatting demonstrates excellent quality and speed in novel view synthesis. Nevertheless, the huge file size of the 3D Gaussians presents challenges for transmission and storage. Current works design compact models to replace…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Shuzhao Xie , Weixiang Zhang , Chen Tang , Yunpeng Bai , Rongwei Lu , Shijia Ge , Zhi Wang

The 3D Gaussian splatting methods are getting popular. However, they work directly on the signal, leading to a dense representation of the signal. Even with some techniques such as pruning or distillation, the results are still dense. In…

Computer Vision and Pattern Recognition · Computer Science 2024-05-10 Yuanhao Gong

3D Gaussian splats have emerged as a revolutionary, effective, learned representation for static 3D scenes. In this work, we explore using 2D Gaussian splats as a new primitive for representing videos. We propose GSVC, an approach to…

Computer Vision and Pattern Recognition · Computer Science 2025-01-23 Longan Wang , Yuang Shi , Wei Tsang Ooi

3D Gaussian Splatting (3DGS) has begun incorporating rich information from 2D foundation models. However, most approaches rely on a bottom-up optimization process that treats raw 2D features as ground truth, incurring increased…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Hyunjoon Lee , Joonkyu Min , Jaesik Park

3D Gaussian Splatting (3DGS) has emerged as a powerful explicit representation enabling real-time, high-fidelity 3D reconstruction and novel view synthesis. However, its practical use is hindered by the massive memory and computational…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Seokhyun Youn , Soohyun Lee , Geonho Kim , Weeyoung Kwon , Sung-Ho Bae , Jihyong Oh

We present the first unified framework for rate-distortion-optimized compression and segmentation of 3D Gaussian Splatting (3DGS). While 3DGS has proven effective for both real-time rendering and semantic scene understanding, prior works…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Yu-Jen Tseng , Chia-Hao Kao , Jing-Zhong Chen , Alessandro Gnutti , Shao-Yuan Lo , Yen-Yu Lin , Wen-Hsiao Peng

3D Gaussian splatting (3DGS) has enabled various applications in 3D scene representation and novel view synthesis due to its efficient rendering capabilities. However, 3DGS demands relatively significant GPU memory, limiting its use on…

Computer Vision and Pattern Recognition · Computer Science 2025-06-05 Hengyu Liu , Yuehao Wang , Chenxin Li , Ruisi Cai , Kevin Wang , Wuyang Li , Pavlo Molchanov , Peihao Wang , Zhangyang Wang

3D Gaussian Splatting is a novel method for 3D view synthesis, which can gain an implicit neural learning rendering result than the traditional neural rendering technology but keep the more high-definition fast rendering speed. But it is…

Computer Vision and Pattern Recognition · Computer Science 2024-05-13 Jinwei Lin

3D Gaussian Splatting (3D-GS) is a recent 3D scene reconstruction technique that enables real-time rendering of novel views by modeling scenes as parametric point clouds of differentiable 3D Gaussians. However, its rendering speed and model…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Alex Hanson , Allen Tu , Geng Lin , Vasu Singla , Matthias Zwicker , Tom Goldstein