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3D Gaussian Splatting (3DGS) has revolutionized fast novel view synthesis, yet its opacity-based formulation makes surface extraction fundamentally difficult. Unlike implicit methods built on Signed Distance Fields or occupancy, 3DGS lacks…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Diego Gomez , Antoine Guédon , Nissim Maruani , Bingchen Gong , Maks Ovsjanikov

This paper introduces SO(2)-Equivariant Gaussian Sculpting Networks (GSNs) as an approach for SO(2)-Equivariant 3D object reconstruction from single-view image observations. GSNs take a single observation as input to generate a Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Ruihan Xu , Anthony Opipari , Joshua Mah , Stanley Lewis , Haoran Zhang , Hanzhe Guo , Odest Chadwicke Jenkins

The 3D Gaussian Splatting technique has significantly advanced the construction of radiance fields from multi-view images, enabling real-time rendering. While point-based rasterization effectively reduces computational demands for…

Computer Vision and Pattern Recognition · Computer Science 2024-06-27 Jiaze Li , Zhengyu Wen , Luo Zhang , Jiangbei Hu , Fei Hou , Zhebin Zhang , Ying He

In the fields of photogrammetry, computer vision and computer graphics, the task of neural 3D scene reconstruction has led to the exploration of various techniques. Among these, 3D Gaussian Splatting stands out for its explicit…

Computer Vision and Pattern Recognition · Computer Science 2024-05-06 Miriam Jäger , Theodor Kapler , Michael Feßenbecker , Felix Birkelbach , Markus Hillemann , Boris Jutzi

3D Gaussian Splatting (3DGS) has revolutionized 3D scene reconstruction, which effectively balances rendering quality, efficiency, and speed. However, existing 3DGS approaches usually generate plausible outputs and face significant…

Graphics · Computer Science 2025-07-22 Beizhen Zhao , Yifan Zhou , Sicheng Yu , Zijian Wang , Hao Wang

In large-scale scene reconstruction using 3D Gaussian splatting, it is common to partition the scene into multiple smaller regions and reconstruct them individually. However, existing division methods are occlusion-agnostic, meaning that…

Graphics · Computer Science 2025-12-02 Shiyong Liu , Xiao Tang , Zhihao Li , Yingfan He , Chongjie Ye , Jianzhuang Liu , Binxiao Huang , Shunbo Zhou , Xiaofei Wu

This paper proposes a novel framework for large-scale scene reconstruction based on 3D Gaussian splatting (3DGS) and aims to address the scalability and accuracy challenges faced by existing methods. For tackling the scalability issue, we…

Computer Vision and Pattern Recognition · Computer Science 2024-09-25 Hanyue Zhang , Zhiliu Yang , Xinhe Zuo , Yuxin Tong , Ying Long , Chen Liu

Novel view synthesis has experienced significant advancements owing to increasingly capable NeRF- and 3DGS-based methods. However, reflective object reconstruction remains challenging, lacking a proper solution to achieve real-time,…

Computer Vision and Pattern Recognition · Computer Science 2025-02-04 Yuxuan Yao , Zixuan Zeng , Chun Gu , Xiatian Zhu , Li Zhang

Omnidirectional (or 360-degree) images are increasingly being used for 3D applications since they allow the rendering of an entire scene with a single image. Existing works based on neural radiance fields demonstrate successful 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Suyoung Lee , Jaeyoung Chung , Jaeyoo Huh , Kyoung Mu Lee

3D Gaussian Splatting is capable of reconstructing 3D scenes in minutes. Despite recent advances in improving surface reconstruction accuracy, the reconstructed results still exhibit bias and suffer from inefficiency in storage and…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Weixing Zhang , Zongrui Li , De Ma , Huajin Tang , Xudong Jiang , Qian Zheng , Gang Pan

We introduce a novel framework for reconstructing dynamic human-object interactions from monocular video that overcomes challenges associated with occlusions and temporal inconsistencies. Traditional 3D reconstruction methods typically…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Hyungjun Doh , Dong In Lee , Seunggeun Chi , Pin-Hao Huang , Kwonjoon Lee , Sangpil Kim , Karthik Ramani

Recently, reconstructing scenes from a single panoramic image using advanced 3D Gaussian Splatting (3DGS) techniques has attracted growing interest. Panoramic images offer a 360$\times$ 180 field of view (FoV), capturing the entire scene in…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Zhijie Shen , Chunyu Lin , Shujuan Huang , Lang Nie , Kang Liao , Yao Zhao

3D Gaussian Splatting (3DGS) has shown remarkable potential for static scene reconstruction, and recent advancements have extended its application to dynamic scenes. However, the quality of reconstructions depends heavily on high-quality…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Yiren Lu , Yunlai Zhou , Disheng Liu , Tuo Liang , Yu Yin

3D Gaussian Splatting techniques have enabled efficient photo-realistic rendering of static scenes. Recent works have extended these approaches to support surface reconstruction and tracking. However, tracking dynamic surfaces with 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Chengwei Zheng , Lixin Xue , Juan Zarate , Jie Song

3D Gaussian Splatting (3D-GS) is a recent 3D scene reconstruction technique that enables real-time rendering of novel views by modeling scenes as parametric point clouds of differentiable 3D Gaussians. However, its rendering speed and model…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Alex Hanson , Allen Tu , Geng Lin , Vasu Singla , Matthias Zwicker , Tom Goldstein

Recent advances in novel view synthesis (NVS) have enabled real-time rendering with 3D Gaussian Splatting (3DGS). However, existing methods struggle with artifacts and missing regions when rendering from viewpoints that deviate from the…

Computer Vision and Pattern Recognition · Computer Science 2025-08-11 Minsu Kim , Subin Jeon , In Cho , Mijin Yoo , Seon Joo Kim

TL;DR: Gaussian Splatting is a widely adopted approach for 3D scene representation, offering efficient, high-quality reconstruction and rendering. A key reason for its success is the simplicity of representing scenes with sets of Gaussians,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Jiahuan Cheng , Jan-Nico Zaech , Luc Van Gool , Danda Pani Paudel

High-fidelity 3D reconstruction of common indoor scenes is crucial for VR and AR applications. 3D Gaussian splatting, a novel differentiable rendering technique, has achieved state-of-the-art novel view synthesis results with high rendering…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Matias Turkulainen , Xuqian Ren , Iaroslav Melekhov , Otto Seiskari , Esa Rahtu , Juho Kannala

Following the advent of NeRFs, 3D Gaussian Splatting (3D-GS) has paved the way to real-time neural rendering overcoming the computational burden of volumetric methods. Following the pioneering work of 3D-GS, several methods have attempted…

Computer Vision and Pattern Recognition · Computer Science 2024-05-01 Evangelos Ververas , Rolandos Alexandros Potamias , Jifei Song , Jiankang Deng , Stefanos Zafeiriou

While novel view synthesis for dynamic scenes has made significant progress, capturing skeleton models of objects and re-posing them remains a challenging task. To tackle this problem, in this paper, we propose a novel approach to…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Diwen Wan , Yuxiang Wang , Ruijie Lu , Gang Zeng