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3D Gaussian Splatting (3DGS) achieves state-of-the-art image quality and real-time performance in novel view synthesis but often suffers from a suboptimal spatial distribution of primitives. This issue stems from cloning-based…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Bartłomiej Baranowski , Stefano Esposito , Patricia Gschoßmann , Anpei Chen , Andreas Geiger

Scene understanding based on 3D Gaussian Splatting (3DGS) has recently achieved notable advances. Although 3DGS related methods have efficient rendering capabilities, they fail to address the inherent contradiction between the anisotropic…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Q. G. Duan , Benyun Zhao , Mingqiao Han Yijun Huang , Ben M. Chen

3D Gaussian Splatting (3DGS) has revolutionized radiance field reconstruction by achieving high-quality novel view synthesis with fast rendering speed, introducing 3D Gaussian primitives to represent the scene. However, 3DGS encounters…

Graphics · Computer Science 2025-09-18 Yifan Mo , Youcheng Cai , Ligang Liu

3D Gaussian Splatting (3D-GS) technique couples 3D Gaussian primitives with differentiable rasterization to achieve high-quality novel view synthesis results while providing advanced real-time rendering performance. However, due to the flaw…

Computer Vision and Pattern Recognition · Computer Science 2024-04-17 Zongxin Ye , Wenyu Li , Sidun Liu , Peng Qiao , Yong Dou

In recent years, Neural Radiance Fields (NeRF) has revolutionized three-dimensional (3D) reconstruction with its implicit representation. Building upon NeRF, 3D Gaussian Splatting (3D-GS) has departed from the implicit representation of…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Bin Zhang , Bi Zeng , Zexin Peng

Decomposing geometry, materials and lighting from a set of images, namely inverse rendering, has been a long-standing problem in computer vision and graphics. Recent advances in neural rendering enable photo-realistic and plausible inverse…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Silong Yong , Venkata Nagarjun Pudureddiyur Manivannan , Bernhard Kerbl , Zifu Wan , Simon Stepputtis , Katia Sycara , Yaqi Xie

3D Gaussian Splatting (3DGS) has gained significant attention for its real-time, photo-realistic rendering in novel-view synthesis and 3D modeling. However, existing methods struggle with accurately modeling in-the-wild scenes affected by…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Chuanyu Fu , Guanying Chen , Yuqi Zhang , Kunbin Yao , Yuan Xiong , Chuan Huang , Shuguang Cui , Yasuyuki Matsushita , Xiaochun Cao

Reconstructing 3D scenes from sparse images remains a challenging task due to the difficulty of recovering accurate geometry and texture without optimization. Recent approaches leverage generalizable models to generate 3D scenes using 3D…

Computer Vision and Pattern Recognition · Computer Science 2026-02-04 Bing He , Jingnan Gao , Yunuo Chen , Ning Cao , Gang Chen , Zhengxue Cheng , Li Song , Wenjun Zhang

Endoluminal endoscopic procedures are essential for diagnosing colorectal cancer and other severe conditions in the digestive tract, urogenital system, and airways. 3D reconstruction and novel-view synthesis from endoscopic images are…

Recently, 3D Gaussian Splatting (3DGS), an explicit scene representation technique, has shown significant promise for dynamic novel-view synthesis from monocular video input. However, purely data-driven 3DGS often struggles to capture the…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Haoqin Hong , Ding Fan , Fubin Dou , Zhi-Li Zhou , Haoran Sun , Congcong Zhu , Jingrun Chen

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

Rendering high-fidelity images from sparse point clouds is still challenging. Existing learning-based approaches suffer from either hole artifacts, missing details, or expensive computations. In this paper, we propose a novel framework to…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Jiaxu Wang , Ziyi Zhang , Junhao He , Renjing Xu

3D Gaussian Splatting has achieved remarkable success in reconstructing both static and dynamic 3D scenes. However, in a scene represented by 3D Gaussian primitives, interactions between objects suffer from inaccurate 3D segmentation,…

Graphics · Computer Science 2025-06-10 Zeyu Xiao , Zhenyi Wu , Mingyang Sun , Qipeng Yan , Yufan Guo , Zhuoer Liang , Lihua Zhang

The recently developed Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) have shown encouraging and impressive results for visual SLAM. However, most representative methods require RGBD sensors and are only available for indoor…

Computer Vision and Pattern Recognition · Computer Science 2025-05-16 Zhe Xin , Chenyang Wu , Penghui Huang , Yanyong Zhang , Yinian Mao , Guoquan Huang

Integrating inverse rendering with multi-view photometric stereo (MVPS) yields more accurate 3D reconstructions than the inverse rendering approaches that rely on fixed environment illumination. However, efficient inverse rendering with…

Graphics · Computer Science 2025-07-25 Yixiao Chen , Bin Liang , Hanzhi Guo , Yongqing Cheng , Jiayi Zhao , Dongdong Weng

Undoing the image formation process and therefore decomposing appearance into its intrinsic properties is a challenging task due to the under-constraint nature of this inverse problem. While significant progress has been made on inferring…

Computer Vision and Pattern Recognition · Computer Science 2015-11-16 Konstantinos Rematas , Tobias Ritschel , Mario Fritz , Efstratios Gavves , Tinne Tuytelaars

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

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

Reconstructing complex reflections in real-world scenes from 2D images is essential for achieving photorealistic novel view synthesis. Existing methods that utilize environment maps to model reflections from distant lighting often struggle…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Tao Xie , Xi Chen , Zhen Xu , Yiman Xie , Yudong Jin , Yujun Shen , Sida Peng , Hujun Bao , Xiaowei Zhou

The advent of neural 3D Gaussians has recently brought about a revolution in the field of neural rendering, facilitating the generation of high-quality renderings at real-time speeds. However, the explicit and discrete representation…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Yingwenqi Jiang , Jiadong Tu , Yuan Liu , Xifeng Gao , Xiaoxiao Long , Wenping Wang , Yuexin Ma