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Recent advancements in 3D Gaussian Splatting (3DGS) have greatly influenced neural fields, as it enables high-fidelity rendering with impressive visual quality. However, 3DGS has difficulty accurately representing surfaces. In contrast,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Haofan Ren , Qingsong Yan , Ming Lu , Rongfeng Lu , Zunjie Zhu

The advent of 3D Gaussian Splatting (3DGS) has recently brought about a revolution in the field of neural rendering, facilitating high-quality renderings at real-time speed. However, 3DGS heavily depends on the initialized point cloud…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 Kai Cheng , Xiaoxiao Long , Kaizhi Yang , Yao Yao , Wei Yin , Yuexin Ma , Wenping Wang , Xuejin Chen

3D Gaussian Splatting (3DGS) renders pixels by rasterizing Gaussian primitives, where the rendering resolution and the primitive number, concluded as the optimization complexity, dominate the time cost in primitive optimization. In this…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Youyu Chen , Junjun Jiang , Kui Jiang , Xiao Tang , Zhihao Li , Xianming Liu , Yinyu Nie

3D Gaussian Splatting (3DGS) has advanced radiance field reconstruction by enabling real-time rendering. However, its reliance on Gaussian kernels for geometry and low-order Spherical Harmonics (SH) for color encoding limits its ability to…

Computer Vision and Pattern Recognition · Computer Science 2025-05-07 Rong Liu , Dylan Sun , Meida Chen , Yue Wang , Andrew Feng

In this paper, we introduce a 3D Gaussian Splatting (3DGS)-based pipeline for stereo dataset generation, offering an efficient alternative to Neural Radiance Fields (NeRF)-based methods. To obtain useful geometry estimates, we explore…

Computer Vision and Pattern Recognition · Computer Science 2025-06-06 Filip Slezak , Magnus K. Gjerde , Joakim B. Haurum , Ivan Nikolov , Morten S. Laursen , Thomas B. Moeslund

Sparse-view synthesis remains a challenging problem due to the difficulty of recovering accurate geometry and appearance from limited observations. While recent advances in 3D Gaussian Splatting (3DGS) have enabled real-time rendering with…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Yi-Hsin Li , Thomas Sikora , Sebastian Knorr , Mårten Sjöström

Although 3D Gaussian Splatting (3D-GS) achieves efficient rendering for novel view synthesis, extending it to dynamic scenes still results in substantial memory overhead from replicating Gaussians across frames. To address this challenge,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Chun-Tin Wu , Jun-Cheng Chen

Retrospective novel view synthesis (NVS) of dynamic scenes is fundamental to applications such as sports. Recent dynamic 3D Gaussian Splatting (3DGS) approaches introduce temporally coupled formulations to enforce motion coherence across…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Yunxiao Zhang , Suryansh Kumar

3D Gaussian Splatting (3DGS) has exhibited remarkable efficacy in novel view synthesis (NVS). However, it suffers from a significant drawback: achieving high-fidelity rendering typically necessitates a large number of 3D Gaussians,…

Computer Vision and Pattern Recognition · Computer Science 2025-08-20 Lintao Xiang , Xinkai Chen , Jianhuang Lai , Guangcong Wang

Recently, 3D Gaussian Splatting (3DGS) has emerged as a prominent framework for novel view synthesis, providing high fidelity and rapid rendering speed. However, the substantial data volume of 3DGS and its attributes impede its practical…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Taorui Wang , Zitong Yu , Yong Xu

The field of 3D reconstruction from images has rapidly evolved in the past few years, first with the introduction of Neural Radiance Field (NeRF) and more recently with 3D Gaussian Splatting (3DGS). The latter provides a significant edge…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Avinash Paliwal , Wei Ye , Jinhui Xiong , Dmytro Kotovenko , Rakesh Ranjan , Vikas Chandra , Nima Khademi Kalantari

Recently, 3D Gaussian Splatting (3DGS) has emerged as a significant advancement in 3D scene reconstruction, attracting considerable attention due to its ability to recover high-fidelity details while maintaining low complexity. Despite the…

Computer Vision and Pattern Recognition · Computer Science 2025-04-10 Qiqi Hou , Randall Rauwendaal , Zifeng Li , Hoang Le , Farzad Farhadzadeh , Fatih Porikli , Alexei Bourd , Amir Said

Generalizable 3D Gaussian Splatting reconstruction showcases advanced Image-to-3D content creation but requires substantial computational resources and large datasets, posing challenges to training models from scratch. Current methods…

Computer Vision and Pattern Recognition · Computer Science 2026-01-05 Xiufeng Huang , Ka Chun Cheung , Runmin Cong , Simon See , Renjie Wan

The problem of 3D reconstruction from posed images is undergoing a fundamental transformation, driven by continuous advances in 3D Gaussian Splatting (3DGS). By modeling scenes explicitly as collections of 3D Gaussians, 3DGS enables…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Vitor Pereira Matias , Daniel Perazzo , Vinicius Silva , Alberto Raposo , Luiz Velho , Afonso Paiva , Tiago Novello

We propose Quadratic Gaussian Splatting (QGS), a novel representation that replaces static primitives with deformable quadric surfaces (e.g., ellipse, paraboloids) to capture intricate geometry. Unlike prior works that rely on Euclidean…

Computer Vision and Pattern Recognition · Computer Science 2025-08-19 Ziyu Zhang , Binbin Huang , Hanqing Jiang , Liyang Zhou , Xiaojun Xiang , Shunhan Shen

Gaussian Splatting (GS) has proven to be highly effective in novel view synthesis, achieving high-quality and real-time rendering. However, its potential for reconstructing detailed 3D shapes has not been fully explored. Existing methods…

Graphics · Computer Science 2024-06-25 Baowen Zhang , Chuan Fang , Rakesh Shrestha , Yixun Liang , Xiaoxiao Long , Ping Tan

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

Digitizing 3D static scenes and 4D dynamic events from multi-view images has long been a challenge in computer vision and graphics. Recently, 3D Gaussian Splatting (3DGS) has emerged as a practical and scalable reconstruction method,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-18 Marko Mihajlovic , Sergey Prokudin , Siyu Tang , Robert Maier , Federica Bogo , Tony Tung , Edmond Boyer

3D Gaussian Splatting (3DGS) has revolutionized novel view synthesis with high-quality rendering through continuous aggregations of millions of 3D Gaussian primitives. However, it suffers from a substantial memory footprint, particularly…

Computer Vision and Pattern Recognition · Computer Science 2026-04-27 Yangming Zhang , Jian Xu , Chaojian Li , Kunxiong Zhu , Wei Niu , Gagan Agrawal , Yang Katie Zhao , Jian Wang , Yingyan Celine Lin , Miao Yin

Low-resolution (LR) multi-view capture limits the fidelity of 3D Gaussian Splatting (3DGS). 3DGS super-resolution (SR) is therefore important, yet challenging because it must recover missing high-frequency details while enforcing cross-view…

Computer Vision and Pattern Recognition · Computer Science 2026-03-23 Xiang Feng , Yongbo He , Linxi Chen , Yan Yang , Chengkai Wang , Yifei Chen , Yixuan Zhong , Zhenzhong Kuang , Jiajun ding , Xufei Yin , Yanming Zhu
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