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3D Gaussian splatting (3DGS) has demonstrated exceptional performance in image-based 3D reconstruction and real-time rendering. However, regions with complex textures require numerous Gaussians to capture significant color variations…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Binxiao Huang , Zhihao Li , Shiyong Liu , Xiao Tang , Jiajun Tang , Jiaqi Lin , Yuxin Cheng , Zhenyu Chen , Xiaofei Wu , Ngai Wong

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) has demonstrated impressive Novel View Synthesis (NVS) results in a real-time rendering manner. During training, it relies heavily on the average magnitude of view-space positional gradients to grow Gaussians to…

Computer Vision and Pattern Recognition · Computer Science 2024-12-09 Qingshan Xu , Jiequan Cui , Xuanyu Yi , Yuxuan Wang , Yuan Zhou , Yew-Soon Ong , Hanwang Zhang

Recent advancements in dynamic 3D scene reconstruction have shown promising results, enabling high-fidelity 3D novel view synthesis with improved temporal consistency. Among these, 4D Gaussian Splatting (4DGS) has emerged as an appealing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Seungjun Oh , Younggeun Lee , Hyejin Jeon , Eunbyung Park

3D Gaussian Splatting (3DGS) has emerged as a powerful representation for real-time, high-performance rendering, enabling a wide range of applications. However, representing 3D scenes with numerous explicit Gaussian primitives imposes…

Computer Vision and Pattern Recognition · Computer Science 2025-11-07 Joo Chan Lee , Jong Hwan Ko , Eunbyung Park

3D Gaussian Splatting (3DGS) has emerged as a prominent framework for real-time, photorealistic scene reconstruction, offering significant speed-ups over Neural Radiance Fields (NeRF). However, the fidelity of 3DGS representations remains…

Image and Video Processing · Electrical Eng. & Systems 2026-05-15 Julien Zouein , Vibhoothi Vibhoothi , François Pitié , Anil Kokaram

Recently, 3D Gaussian Splatting (3DGS) has revolutionized radiance field reconstruction, manifesting efficient and high-fidelity novel view synthesis. However, accurately representing surfaces, especially in large and complex scenarios,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-05 Yang Liu , Chuanchen Luo , Zhongkai Mao , Junran Peng , Zhaoxiang Zhang

3D Gaussian Splatting (3DGS) has revolutionized neural rendering with its efficiency and quality, but like many novel view synthesis methods, it heavily depends on accurate camera poses from Structure-from-Motion (SfM) systems. Although…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Zhisheng Huang , Peng Wang , Jingdong Zhang , Yuan Liu , Xin Li , Wenping Wang

3D Gaussian Splatting represents a breakthrough in the field of novel view synthesis. It establishes Gaussians as core rendering primitives for highly accurate real-world environment reconstruction. Recent advances have drastically…

Graphics · Computer Science 2025-06-25 Jonathan Haberl , Philipp Fleck , Clemens Arth

Standard 3D Gaussian Splatting (3DGS) relies on known or pre-computed camera poses and a sparse point cloud, obtained from structure-from-motion (SfM) preprocessing, to initialize and grow 3D Gaussians. We propose a novel SfM-Free 3DGS…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Bo Ji , Angela Yao

3D Gaussian Splatting (3DGS) has made remarkable progress in RGBD SLAM. Current methods usually use 3D Gaussians or view-tied 3D Gaussians to represent radiance fields in tracking and mapping. However, these Gaussians are either too…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Pengchong Hu , Zhizhong Han

3D Gaussian splatting (3DGS) is a popular radiance field method, with many application-specific extensions. Most variants rely on the same core algorithm: depth-sorting of Gaussian splats then rasterizing in primitive order. This ensures…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Shakiba Kheradmand , Delio Vicini , George Kopanas , Dmitry Lagun , Kwang Moo Yi , Mark Matthews , Andrea Tagliasacchi

In underwater images, most useful features are occluded by water. The extent of the occlusion depends on imaging geometry and can vary even across a sequence of burst images. As a result, 3D reconstruction methods robust on in-air scenes,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Nir Mualem , Roy Amoyal , Oren Freifeld , Derya Akkaynak

We present FlashSLAM, a novel SLAM approach that leverages 3D Gaussian Splatting for efficient and robust 3D scene reconstruction. Existing 3DGS-based SLAM methods often fall short in sparse view settings and during large camera movements…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Phu Pham , Damon Conover , Aniket Bera

Real-time rendering of dynamic scenes with view-dependent effects remains a fundamental challenge in computer graphics. While recent advances in Gaussian Splatting have shown promising results separately handling dynamic scenes (4DGS) and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Zhongpai Gao , Benjamin Planche , Meng Zheng , Anwesa Choudhuri , Terrence Chen , Ziyan Wu

3D Gaussian Splatting (3DGS) has emerged as a cutting-edge technique for real-time radiance field rendering, offering state-of-the-art performance in terms of both quality and speed. 3DGS models a scene as a collection of three-dimensional…

Computer Vision and Pattern Recognition · Computer Science 2025-03-06 Milena T. Bagdasarian , Paul Knoll , Yi-Hsin Li , Florian Barthel , Anna Hilsmann , Peter Eisert , Wieland Morgenstern

3D Gaussian Splatting (3DGS) enables fast, high-quality novel view synthesis but typically relies on densification followed by pruning to optimize the number of Gaussians. Existing mask-based pruning, such as MaskGS, regularizes the global…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Ashkan Taghipour , Vahid Naghshin , Benjamin Southwell , Farid Boussaid , Hamid Laga , Mohammed Bennamoun

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

Feed-forward 3D Gaussian Splatting (FF-3DGS) emerges as a fast and robust solution for sparse-view 3D reconstruction and novel view synthesis (NVS). However, existing FF-3DGS methods are built on incorrect screen-space dilation filters,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Taewoo Suh , Sungpyo Kim , Jongmin Park , Munchurl Kim

3D Gaussian Splat (3DGS) enables high-fidelity, real-time novel view synthesis by representing scenes with large sets of anisotropic primitives, but often requires millions of Splats, incurring significant storage and transmission costs.…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Butian Xiong , Rong Liu , Tiantian Zhou , Meida Chen , Zhiwen Fan , Andrew Feng
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