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Scene change detection methods built on Gaussian splatting universally follow a render-then-compare paradigm: the pre-change scene is rendered into 2D and compared against post-change images via pixel or feature residuals. This change…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Chamuditha Jayanga Galappaththige , Jason Lai , Timothy Patten , Donald Dansereau , Niko Suenderhauf , Dimity Miller

Conventional geometry-based SLAM systems lack dense 3D reconstruction capabilities since their data association usually relies on feature correspondences. Additionally, learning-based SLAM systems often fall short in terms of real-time…

Computer Vision and Pattern Recognition · Computer Science 2024-08-22 Zhongche Qu , Zhi Zhang , Cong Liu , Jianhua Yin

Three-dimensional Gaussian Splatting (3DGS) has recently emerged as an efficient representation for novel-view synthesis, achieving impressive visual quality. However, in scenes dominated by large and low-texture regions, common in indoor…

Computer Vision and Pattern Recognition · Computer Science 2025-10-29 Xirui Jin , Renbiao Jin , Boying Li , Danping Zou , Wenxian Yu

3D Gaussian Splatting (GS) has emerged as a powerful representation for high-quality scene reconstruction, offering compelling rendering quality. However, the training process of GS often suffers from slow convergence due to inefficient…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Binxiao Huang , Zhengwu Liu , Ngai Wong

Reconstructing dynamic scenes from video sequences is a highly promising task in the multimedia domain. While previous methods have made progress, they often struggle with slow rendering and managing temporal complexities such as…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Jinbo Yan , Rui Peng , Luyang Tang , Ronggang Wang

Ray-tracing-based 3D Gaussian splatting (3DGS) methods overcome the limitations of rasterization -- rigid pinhole camera assumptions, inaccurate shadows, and lack of native reflection or refraction -- but remain slower due to the cost of…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Peiyu Xu , Xin Sun , Krishna Mullia , Raymond Fei , Iliyan Georgiev , Shuang Zhao

3D Gaussian splatting (3DGS) has demonstrated impressive performance in synthesizing high-fidelity novel views. Nonetheless, its effectiveness critically depends on the quality of the initialized point cloud. Specifically, achieving uniform…

Computer Vision and Pattern Recognition · Computer Science 2025-10-13 Yikang Zhang , Rui Fan

3D Gaussian Splatting (3DGS) has attracted great attention in novel view synthesis because of its superior rendering efficiency and high fidelity. However, the trained Gaussians suffer from severe zooming degradation due to non-adjustable…

Computer Vision and Pattern Recognition · Computer Science 2024-08-13 Jiameng Li , Yue Shi , Jiezhang Cao , Bingbing Ni , Wenjun Zhang , Kai Zhang , Luc Van Gool

We propose GS-LRM, a scalable large reconstruction model that can predict high-quality 3D Gaussian primitives from 2-4 posed sparse images in 0.23 seconds on single A100 GPU. Our model features a very simple transformer-based architecture;…

Computer Vision and Pattern Recognition · Computer Science 2024-05-01 Kai Zhang , Sai Bi , Hao Tan , Yuanbo Xiangli , Nanxuan Zhao , Kalyan Sunkavalli , Zexiang Xu

3D Gaussian Splatting (3DGS) has emerged as a novel explicit representation for 3D scenes, offering both high-fidelity reconstruction and efficient rendering. However, 3DGS lacks 3D segmentation ability, which limits its applicability in…

Computer Vision and Pattern Recognition · Computer Science 2025-08-28 Yupeng Zhang , Dezhi Zheng , Ping Lu , Han Zhang , Lei Wang , Liping xiang , Cheng Luo , Kaijun Deng , Xiaowen Fu , Linlin Shen , Jinbao Wang

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

3D Gaussian Splatting (3DGS) has emerged as a leading technique for novel view synthesis, demonstrating exceptional rendering efficiency. \replaced[]{Well-reconstructed surfaces can be characterized by low configurational entropy, where…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Hong Kuang , Jianchen Liu

While 3D Gaussian Splatting (3DGS) has revolutionized 3D reconstruction, it suffers from significant overhead due to massive redundant primitives. Existing compression methods typically rely on local sampling or fixed pruning thresholds,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Beizhen Zhao , Sicheng Yu , Ziran Yin , Dongxu Shen , Hao Wang

Simultaneous localization and mapping is essential for position tracking and scene understanding. 3D Gaussian-based map representations enable photorealistic reconstruction and real-time rendering of scenes using multiple posed cameras. We…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Lisong C. Sun , Neel P. Bhatt , Jonathan C. Liu , Zhiwen Fan , Zhangyang Wang , Todd E. Humphreys , Ufuk Topcu

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

Gaussian Splatting has revolutionized the world of novel view synthesis by achieving high rendering performance in real-time. Recently, studies have focused on enriching these 3D representations with semantic information for downstream…

Computer Vision and Pattern Recognition · Computer Science 2024-09-02 Mihnea-Bogdan Jurca , Remco Royen , Ion Giosan , Adrian Munteanu

Gaussian Splatting (GS) enables immersive rendering, but realistic 3D object-scene composition remains challenging. Baked appearance and shadow information in GS radiance fields cause inconsistencies when combining objects and scenes.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-10 Jian Gao , Mengqi Yuan , Yifei Zeng , Chang Zeng , Zhihao Li , Zhenyu Chen , Weichao Qiu , Xiao-Xiao Long , Hao Zhu , Xun Cao , Yao Yao

3D Gaussian Splatting has shown fast and high-quality rendering results in static scenes by leveraging dense 3D prior and explicit representations. Unfortunately, the benefits of the prior and representation do not involve novel view…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Junoh Lee , Chang-Yeon Won , Hyunjun Jung , Inhwan Bae , Hae-Gon Jeon

Recent advances in 3D Gaussian Splatting (3DGS) have enabled significant progress in photorealistic novel view synthesis. However, traditional 3DGS relies on a slow, iterative optimization process, which limits its use in scenarios…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Can Wang , Lei Liu , Wei Jiang , Dong Xu

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