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While Dynamic Gaussian Splatting enables high-fidelity 4D reconstruction, its deployment is severely hindered by a fundamental dilemma: unconstrained densification leads to excessive memory consumption incompatible with edge devices,…

Computer Vision and Pattern Recognition · Computer Science 2026-02-04 Zihan Zheng , Zhenglong Wu , Xuanxuan Wang , Houqiang Zhong , Xiaoyun Zhang , Qiang Hu , Guangtao Zhai , Wenjun Zhang

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

3D Gaussian Splatting (3DGS) has made significant strides in novel view synthesis but is limited by the substantial number of Gaussian primitives required, posing challenges for deployment on lightweight devices. Recent methods address this…

Computer Vision and Pattern Recognition · Computer Science 2025-04-09 Zhengqing Gao , Dongting Hu , Jia-Wang Bian , Huan Fu , Yan Li , Tongliang Liu , Mingming Gong , Kun Zhang

Underwater 3D scene reconstruction faces severe challenges from light absorption, scattering, and turbidity, which degrade geometry and color fidelity in traditional methods like Neural Radiance Fields (NeRF). While NeRF extensions such as…

Computer Vision and Pattern Recognition · Computer Science 2025-08-11 Wenpeng Xing , Jie Chen , Zaifeng Yang , Changting Lin , Jianfeng Dong , Chaochao Chen , Xun Zhou , Meng Han

3D Gaussian splatting (3DGS) is an innovative rendering technique that surpasses the neural radiance field (NeRF) in both rendering speed and visual quality by leveraging an explicit 3D scene representation. Existing 3DGS approaches require…

Computer Vision and Pattern Recognition · Computer Science 2025-06-13 Lintao Xiang , Hongpei Zheng , Yating Huang , Qijun Yang , Hujun Yin

3D Gaussian splatting has achieved very impressive performance in real-time novel view synthesis. However, it often suffers from over-reconstruction during Gaussian densification where high-variance image regions are covered by a few large…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Jiahui Zhang , Fangneng Zhan , Muyu Xu , Shijian Lu , Eric Xing

Compression techniques for 3D Gaussian Splatting (3DGS) have recently achieved considerable success in minimizing storage overhead for 3D Gaussians while preserving high rendering quality. Despite the impressive storage reduction, the lack…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Seungjoo Shin , Jaesik Park , Sunghyun Cho

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

High Dynamic Range (HDR) 3D reconstruction is pivotal for professional content creation in filmmaking and virtual production. Existing methods typically rely on multi-exposure Low Dynamic Range (LDR) supervision to constrain the learning…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Kaixuan Zhang , Minxian Li , Mingwu Ren , Jiankang Deng , Xiatian Zhu

Professional color editing requires precise control over both color (hue and saturation) and lightness, ideally through separate, independent controls. We present a real-time interactive color editing framework for 3D Gaussian Splatting…

Graphics · Computer Science 2026-04-03 Cheng-Kang Ted Chao , Yotam Gingold

Empowering 3D Gaussian Splatting with generalization ability is appealing. However, existing generalizable 3D Gaussian Splatting methods are largely confined to narrow-range interpolation between stereo images due to their heavy backbones,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Yunsong Wang , Tianxin Huang , Hanlin Chen , Gim Hee Lee

3D Gaussian Splatting (3DGS) has emerged as a preferred choice alongside Neural Radiance Fields (NeRF) in inverse rendering due to its superior rendering speed. Currently, the common approach in 3DGS is to utilize "single-view" mini-batch…

Computer Vision and Pattern Recognition · Computer Science 2025-06-18 Minhyuk Choi , Injae Kim , Hyunwoo J. Kim

3D Gaussian Splatting (3DGS) leverages densely distributed Gaussian primitives for high-quality scene representation and reconstruction. While existing 3DGS methods perform well in scenes with minor view variation, large view changes from…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Chenhao Zhang , Yuanping Cao , Lei Zhang

We present a novel framework for enhancing the visual fidelity and consistency of text-guided 3D Gaussian Splatting (3DGS) editing. Existing editing approaches face two critical challenges: inconsistent geometric reconstructions across…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Xuanqi Zhang , Jieun Lee , Chris Joslin , Wonsook Lee

3D Gaussian Splatting has emerged as a powerful scene representation for real-time novel-view synthesis. However, its standard adaptive density control relies on screen-space positional gradients, which do not distinguish between geometric…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Linjie Lyu , Ayush Tewari , Jianchun Chen , Thomas Leimkühler , Christian Theobalt

We present a multispectral extension to 3D Gaussian Splatting (3DGS) for wavelength-aware view synthesis. Each Gaussian is augmented with spectral radiance, represented via per-band spherical harmonics, and optimized under a dual-loss…

Computer Vision and Pattern Recognition · Computer Science 2026-04-16 Iris Zheng , Guojun Tang , Alexander Doronin , Paul Teal , Fang-Lue Zhang

3D Gaussian Splatting (3DGS) enables efficient training and fast novel view synthesis in static environments. To address challenges posed by transient objects, distractor-free 3DGS methods have emerged and shown promising results when dense…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Yi Gu , Zhaorui Wang , Jiahang Cao , Jiaxu Wang , Mingle Zhao , Dongjun Ye , Renjing Xu

3D Gaussian Splatting (3DGS) has emerged as a powerful technique for novel view synthesis, demonstrating remarkable capability in high-fidelity scene reconstruction through its Gaussian primitive representations. However, the computational…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Chengbo Wang , Guozheng Ma , Yifei Xue , Yizhen Lao

3D Gaussian Splatting (3DGS) has emerged as a powerful technique for novel view synthesis. However, existing methods struggle to adaptively optimize the distribution of Gaussian primitives based on scene characteristics, making it…

Computer Vision and Pattern Recognition · Computer Science 2025-06-23 Hongbi Zhou , Zhangkai Ni

In this paper, we present a method to optimize Gaussian splatting with a limited number of images while avoiding overfitting. Representing a 3D scene by combining numerous Gaussian splats has yielded outstanding visual quality. However, it…

Computer Vision and Pattern Recognition · Computer Science 2024-01-05 Jaeyoung Chung , Jeongtaek Oh , Kyoung Mu Lee