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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 witnessed exponential adoption across diverse applications, driving a critical need for semantic-aware 3D Gaussian representations to enable scene understanding and editing tasks. Existing approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Zhaonan Wang , Manyi Li , Changhe Tu

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

As an emerging novel view synthesis approach, 3D Gaussian Splatting (3DGS) demonstrates fast training/rendering with superior visual quality. The two tasks of 3DGS, Gaussian creation and view rendering, are typically separated over time or…

Computer Vision and Pattern Recognition · Computer Science 2025-08-15 Yuning Huang , Jiahao Pang , Fengqing Zhu , Dong Tian

Recent advancements in 3D Gaussian Splatting(3DGS) have significantly improved semantic scene understanding, enabling natural language queries to localize objects within a scene. However, existing methods primarily focus on embedding…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Xihan Wang , Dianyi Yang , Yu Gao , Yufeng Yue , Yi Yang , Mengyin Fu

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 (3DGS) achieves impressive rendering fidelity and speed for novel view synthesis. However, its substantial data size poses a significant challenge for practical applications. While many compression techniques have been…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Yihang Chen , Mengyao Li , Qianyi Wu , Weiyao Lin , Mehrtash Harandi , Jianfei Cai

Existing 4D Gaussian Splatting methods rely on per-Gaussian deformation from a canonical space to target frames, which overlooks redundancy among adjacent Gaussian primitives and results in suboptimal performance. To address this…

Computer Vision and Pattern Recognition · Computer Science 2025-05-14 He Huang , Qi Yang , Mufan Liu , Yiling Xu , Zhu Li

3D Gaussian Splatting (3DGS) is a highly deployable real-time method for novel view synthesis. In practice, it requires a universal, consistent control mechanism that adjusts the trade-off between rendering quality and model compression…

Computer Vision and Pattern Recognition · Computer Science 2025-11-10 Fengdi Zhang , Yibao Sun , Hongkun Cao , Ruqi Huang

Recent advances in 3D Gaussian Splatting (3DGS) have demonstrated remarkable capabilities in real-time and photorealistic novel view synthesis. However, traditional 3DGS representations often struggle with large-scale scene management and…

Graphics · Computer Science 2025-08-08 Zijian Wang , Beizhen Zhao , Hao Wang

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 propose R3GS, a robust reconstruction and relocalization framework tailored for unconstrained datasets. Our method uses a hybrid representation during training. Each anchor combines a global feature from a convolutional neural network…

Computer Vision and Pattern Recognition · Computer Science 2025-05-22 Xu yan , Zhaohui Wang , Rong Wei , Jingbo Yu , Dong Li , Xiangde Liu

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) 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

3D Gaussian Splatting has emerged as a transformative technique in novel view synthesis, primarily due to its high rendering speed and photorealistic fidelity. However, its memory footprint scales rapidly with scene complexity, often…

Computer Vision and Pattern Recognition · Computer Science 2025-11-20 Keshav Gupta , Akshat Sanghvi , Shreyas Reddy Palley , Astitva Srivastava , Charu Sharma , Avinash Sharma

3D Gaussian Splatting (3DGS) has become one of the most influential works in the past year. Due to its efficient and high-quality novel view synthesis capabilities, it has been widely adopted in many research fields and applications.…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Glenn Grubert , Florian Barthel , Anna Hilsmann , Peter Eisert

Recent advances in Gaussian Splatting based 3D scene representation have shown two major trends: semantics-oriented approaches that focus on high-level understanding but lack explicit 3D geometry modeling, and structure-oriented approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Yuhang Ming , Chenxin Fang , Xingyuan Yu , Fan Zhang , Weichen Dai , Wanzeng Kong , Guofeng Zhang

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 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 performance in novel view synthesis and 3D scene reconstruction, yet its quality often degrades in real-world environments due to transient distractors, such as moving objects and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Jiahao Chen , Yipeng Qin , Ganlong Zhao , Xin Li , Wenping Wang , Guanbin Li