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The introduction of 3D Gaussian Splatting (3DGS) has advanced novel view synthesis by utilizing Gaussians to represent scenes. Encoding Gaussian point features with anchor embeddings has significantly enhanced the performance of newer 3DGS…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Junyan Su , Baozhu Zhao , Xiaohan Zhang , Qi Liu

3D Gaussian Splatting (3D-GS) achieves real-time photorealistic novel view synthesis, yet struggles with complex scenes due to over-reconstruction artifacts, manifesting as local blurring and needle-shape distortions. While recent…

Computer Vision and Pattern Recognition · Computer Science 2025-10-23 Yuxin Cheng , Binxiao Huang , Wenyong Zhou , Taiqiang Wu , Zhengwu Liu , Graziano Chesi , Ngai Wong

3D Gaussian Splatting (3DGS) has recently emerged as a promising approach in novel view synthesis, combining photorealistic rendering with real-time efficiency. However, its success heavily relies on dense camera coverage; under sparse-view…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Jiashu Li , Xumeng Han , Zhaoyang Wei , Zipeng Wang , Kuiran Wang , Guorong Li , Zhenjun Han , Jianbin Jiao

Recently, 3D Gaussian Splatting (3D-GS) has prevailed in novel view synthesis, achieving high fidelity and efficiency. However, it often struggles to capture rich details and complete geometry. Our analysis reveals that the 3D-GS…

Computer Vision and Pattern Recognition · Computer Science 2025-10-01 Yanzhe Lyu , Kai Cheng , Xin Kang , Xuejin Chen

Recently, the integration of the efficient feed-forward scheme into 3D Gaussian Splatting (3DGS) has been actively explored. However, most existing methods focus on sparse view reconstruction of small regions and cannot produce eligible…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Yunsong Wang , Tianxin Huang , Hanlin Chen , Gim Hee Lee

By adaptively controlling the density and generating more Gaussians in regions with high-frequency information, 3D Gaussian Splatting (3DGS) can better represent scene details. From the signal processing perspective, representing details…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Zhaojie Zeng , Yuesong Wang , Lili Ju , Tao Guan

3D Gaussian Splatting (3DGS) has shown remarkable success in synthesizing novel views given multiple views of a static scene. Yet, 3DGS faces challenges when applied to dynamic scenes because 3D Gaussian parameters need to be updated per…

Graphics · Computer Science 2024-07-08 Kai Katsumata , Duc Minh Vo , Hideki Nakayama

3D Gaussian Splatting (3DGS) has emerged as a mainstream solution for novel view synthesis and 3D reconstruction. By explicitly encoding a 3D scene using a collection of Gaussian kernels, 3DGS achieves high-quality rendering with superior…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Lei Lan , Tianjia Shao , Zixuan Lu , Yu Zhang , Chenfanfu Jiang , Yin Yang

Reconstructing high-quality 3D scenes from low-resolution multi-view images remains challenging for 3D Gaussian Splatting (3DGS), because insufficient high-frequency observations often lead to blurred textures, weak boundaries, and…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Jiaxiang Li , Zongtan Zhou , Zhen Tan , Yadong Liu , Dewen Hu

Recently, 3D Gaussian Splatting has emerged as a prominent research direction owing to its ultrarapid training speed and high-fidelity rendering capabilities. However, the unstructured and irregular nature of Gaussian point clouds poses…

Computer Vision and Pattern Recognition · Computer Science 2026-02-16 Xiao Ren , Yu Liu , Ning An , Jian Cheng , Xin Qiao , He Kong

The dominant 3D Gaussian splatting (3DGS) acceleration methods fail to properly regulate the number of Gaussians during training, causing redundant computational time overhead. In this paper, we propose FastGS, a novel, simple, and general…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Shiwei Ren , Tianci Wen , Yongchun Fang , Biao Lu

3D Gaussian Splatting (3DGS) has emerged as a powerful technique for radiance field rendering, but it typically requires millions of redundant Gaussian primitives, overwhelming memory and rendering budgets. Existing compaction approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-09-26 Tao Wang , Mengyu Li , Geduo Zeng , Cheng Meng , Qiong Zhang

3D Gaussian Splatting (3DGS) has demonstrated remarkable performance in scene synthesis and novel view synthesis tasks. Typically, the initialization of 3D Gaussian primitives relies on point clouds derived from Structure-from-Motion (SfM)…

Computer Vision and Pattern Recognition · Computer Science 2024-09-16 Shan Chen , Jiale Zhou , Lei Li

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

Current 4D Gaussian frameworks for dynamic scene reconstruction deliver impressive visual fidelity and rendering speed, however, the inherent trade-off between storage costs and the ability to characterize complex physical motions…

Graphics · Computer Science 2025-07-11 Wei Yao , Shuzhao Xie , Letian Li , Weixiang Zhang , Zhixin Lai , Shiqi Dai , Ke Zhang , Zhi Wang

3D Gaussian Splatting (3DGS) techniques have recently enabled high-quality 3D scene reconstruction and real-time novel view synthesis. These approaches, however, are limited by the pinhole camera model and lack effective modeling of defocus…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Yujie Wang , Praneeth Chakravarthula , Baoquan Chen

Radiance fields represented by 3D Gaussians excel at synthesizing novel views, offering both high training efficiency and fast rendering. However, with sparse input views, the lack of multi-view consistency constraints results in poorly…

Computer Vision and Pattern Recognition · Computer Science 2025-08-27 Yuru Xiao , Deming Zhai , Wenbo Zhao , Kui Jiang , Junjun Jiang , Xianming Liu

In-the-wild photo collections often contain limited volumes of imagery and exhibit multiple appearances, e.g., taken at different times of day or seasons, posing significant challenges to scene reconstruction and novel view synthesis.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-27 Deming Li , Kaiwen Jiang , Yutao Tang , Ravi Ramamoorthi , Rama Chellappa , Cheng Peng

Recent advancements in 3D editing have highlighted the potential of text-driven methods in real-time, user-friendly AR/VR applications. However, current methods rely on 2D diffusion models without adequately considering multi-view…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Dong In Lee , Hyeongcheol Park , Jiyoung Seo , Eunbyung Park , Hyunje Park , Ha Dam Baek , Sangheon Shin , Sangmin Kim , Sangpil Kim

Efficient scene representations are essential for many real-world applications, especially those involving spatial measurement. Although current NeRF-based methods have achieved impressive results in reconstructing building-scale scenes,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-19 Jianlin Guo , Haihong Xiao , Wenxiong Kang