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High-quality reconstruction is crucial for dense SLAM. Recent popular approaches utilize 3D Gaussian Splatting (3D GS) techniques for RGB, depth, and semantic reconstruction of scenes. However, these methods often overlook issues of detail…

Computer Vision and Pattern Recognition · Computer Science 2024-12-05 Zhenzhong Cao , Chenyang Zhao , Qianyi Zhang , Jinzheng Guang , Yinuo Song Jingtai Liu

3D Gaussian Splatting (3DGS) has emerged as a leading representation for real-time novel view synthesis and has been widely adopted in various downstream applications. The core strength of 3DGS lies in its efficient kernel-based scene…

Computer Vision and Pattern Recognition · Computer Science 2026-05-18 Xiangru Wu , Ke Fan , Yanwei Fu

Embodied intelligence requires precise reconstruction and rendering to simulate large-scale real-world data. Although 3D Gaussian Splatting (3DGS) has recently demonstrated high-quality results with real-time performance, it still faces…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Haodong Xiang , Xinghui Li , Kai Cheng , Xiansong Lai , Wanting Zhang , Zhichao Liao , Long Zeng , Xueping Liu

We present the first application of 3D Gaussian Splatting in monocular SLAM, the most fundamental but the hardest setup for Visual SLAM. Our method, which runs live at 3fps, utilises Gaussians as the only 3D representation, unifying the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Hidenobu Matsuki , Riku Murai , Paul H. J. Kelly , Andrew J. Davison

We present a study of how to integrate color (RGB) and multi-spectral imagery (red, green, red-edge, and near-infrared) into the 3D Gaussian Splatting (3DGS) framework, a state-of-the-art explicit radiance-field-based method for fast and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Josef Grün , Lukas Meyer , Maximilian Weiherer , Bernhard Egger , Marc Stamminger , Linus Franke

Seamless integration of both aerial and street view images remains a significant challenge in neural scene reconstruction and rendering. Existing methods predominantly focus on single domain, limiting their applications in immersive…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Lihan Jiang , Kerui Ren , Mulin Yu , Linning Xu , Junting Dong , Tao Lu , Feng Zhao , Dahua Lin , Bo Dai

Underwater image degradation poses significant challenges for 3D reconstruction, where simplified physical models often fail in complex scenes. We propose \textbf{R-Splatting}, a unified framework that bridges underwater image restoration…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Guoxi Huang , Haoran Wang , Zipeng Qi , Wenjun Lu , David Bull , Nantheera Anantrasirichai

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

Implicit Neural Representations (INR) have been successfully employed for Arbitrary-scale Super-Resolution (ASR). However, INR-based models need to query the multi-layer perceptron module numerous times and render a pixel in each query,…

Image and Video Processing · Electrical Eng. & Systems 2025-07-31 Du Chen , Liyi Chen , Zhengqiang Zhang , Lei Zhang

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

Recent works in volume rendering, \textit{e.g.} NeRF and 3D Gaussian Splatting (3DGS), significantly advance the rendering quality and efficiency with the help of the learned implicit neural radiance field or 3D Gaussians. Rendering on top…

Computer Vision and Pattern Recognition · Computer Science 2026-02-06 Xiaobiao Du , Yida Wang , Xin Yu

Recent advancements in 3D Gaussian Splatting (3DGS) have made a significant impact on rendering and reconstruction techniques. Current research predominantly focuses on improving rendering performance and reconstruction quality using…

Computer Vision and Pattern Recognition · Computer Science 2025-09-18 Yinlong Bai , Hongxin Zhang , Sheng Zhong , Junkai Niu , Hai Li , Yijia He , Yi Zhou

3D Gaussian Splatting (3DGS) enables high-quality real-time 3D rendering but faces challenges in efficiently scaling to ultra-dense scenes and high-resolution due to computational bottlenecks that limit its use in latency-sensitive…

Graphics · Computer Science 2026-05-13 Yibo Zhao , Fan Gao , Youcheng Cai , Ligang Liu

The recent introduction of 3D Gaussian Splatting (3DGS) has significantly advanced novel view synthesis. Several studies have further improved the rendering quality of 3DGS, yet they still exhibit noticeable visual discrepancies when…

Computer Vision and Pattern Recognition · Computer Science 2025-11-20 Junseo Koo , Jinseo Jeong , Gunhee Kim

3D reconstruction from multi-view images is one of the fundamental challenges in computer vision and graphics. Recently, 3D Gaussian Splatting (3DGS) has emerged as a promising technique capable of real-time rendering with high-quality 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Junha Hyung , Susung Hong , Sungwon Hwang , Jaeseong Lee , Jaegul Choo , Jin-Hwa Kim

While 3D Gaussian Splatting (3DGS) enabled photorealistic mapping, its integration into SLAM has largely followed traditional camera-centric pipelines. As a result, they inherit well-known weaknesses such as high computational load, failure…

Robotics · Computer Science 2026-03-10 Jaeseok Park , Chanoh Park , Minsu Kim , Minkyoung Kim , Soohwan Kim

Reconstructing high-fidelity underwater scenes remains a challenging task due to light absorption, scattering, and limited visibility inherent in aquatic environments. This paper presents an enhanced Gaussian Splatting-based framework that…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Zhuodong Jiang , Haoran Wang , Guoxi Huang , Brett Seymour , Nantheera Anantrasirichai

A well-designed vectorized representation is crucial for the learning systems natively based on 3D Gaussian Splatting. While 3DGS enables efficient and explicit 3D reconstruction, its parameter-based representation remains hard to learn as…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Yuelin Xin , Yuheng Liu , Xiaohui Xie , Xinke Li

Dynamic novel view synthesis (NVS) is essential for creating immersive experiences. Existing approaches have advanced dynamic NVS by introducing 3D Gaussian Splatting (3DGS) with implicit deformation fields or indiscriminately assigned…

Computer Vision and Pattern Recognition · Computer Science 2025-12-17 Kaizhe Zhang , Yijie Zhou , Weizhan Zhang , Caixia Yan , Haipeng Du , yugui xie , Yu-Hui Wen , Yong-Jin Liu

Recent advances in novel view synthesis have enabled real-time rendering speeds with high reconstruction accuracy. 3D Gaussian Splatting (3D-GS), a foundational point-based parametric 3D scene representation, models scenes as large sets of…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Alex Hanson , Allen Tu , Vasu Singla , Mayuka Jayawardhana , Matthias Zwicker , Tom Goldstein