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Gaussian Splatting has emerged as a leading method for novel view synthesis, offering superior training efficiency and real-time inference compared to NeRF approaches, while still delivering high-quality reconstructions. Beyond view…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Lorenzo Rutayisire , Nicola Capodieci , Fabio Pellacini

The recent development of 3D Gaussian Splatting (3DGS) has led to great interest in 4D dynamic spatial reconstruction. Existing approaches mainly rely on full-length multi-view videos, while there has been limited exploration of online…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Zhening Liu , Yingdong Hu , Xinjie Zhang , Rui Song , Jiawei Shao , Zehong Lin , Jun Zhang

Recent advancements in 3D Gaussian Splatting (3D-GS) have demonstrated the potential of using 3D Gaussian primitives for high-speed, high-fidelity, and cost-efficient novel view synthesis from continuously calibrated input views. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Jingqian Wu , Shuo Zhu , Chutian Wang , Boxin Shi , Edmund Y. Lam

Neural Radiance Field (NeRF) and 3D Gaussian Splatting (3DGS) have noticeably advanced photo-realistic novel view synthesis using images from densely spaced camera viewpoints. However, these methods struggle in few-shot scenarios due to…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Yulong Zheng , Zicheng Jiang , Shengfeng He , Yandu Sun , Junyu Dong , Huaidong Zhang , Yong Du

3D Gaussian splatting (3DGS) has become a vital tool for learning a radiance field from multiple posed images. Although 3DGS shows great advantages over NeRF in terms of rendering quality and efficiency, it remains a research challenge to…

Computer Vision and Pattern Recognition · Computer Science 2026-03-11 Jiaqi Liu , Zhizhong Han

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

Compared with previous 3D reconstruction methods like Nerf, recent Generalizable 3D Gaussian Splatting (G-3DGS) methods demonstrate impressive efficiency even in the sparse-view setting. However, the promising reconstruction performance of…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Chuanrui Zhang , Yingshuang Zou , Zhuoling Li , Minmin Yi , Haoqian Wang

3D Gaussian Splatting (3DGS) has recently transformed photorealistic reconstruction, achieving high visual fidelity and real-time performance. However, rendering quality significantly deteriorates when test views deviate from the camera…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Yutong Chen , Marko Mihajlovic , Xiyi Chen , Yiming Wang , Sergey Prokudin , Siyu Tang

Novel view synthesis has shown rapid progress recently, with methods capable of producing increasingly photorealistic results. 3D Gaussian Splatting has emerged as a promising method, producing high-quality renderings of scenes and enabling…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Richard Shaw , Michal Nazarczuk , Jifei Song , Arthur Moreau , Sibi Catley-Chandar , Helisa Dhamo , Eduardo Perez-Pellitero

3D Gaussian Splatting (3DGS) has recently emerged as a promising approach in novel view synthesis, combining photorealistic rendering with real-time efficiency. However, its success heavily relies on dense camera coverage; under sparse-view…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Jiashu Li , Xumeng Han , Zhaoyang Wei , Zipeng Wang , Kuiran Wang , Guorong Li , Zhenjun Han , Jianbin Jiao

3D Gaussian Splatting (3DGS) optimization is most commonly performed using standard optimizers (Adam, SGD). While stable across diverse scenes, standard optimizers are general-purpose and not tailored to the structure of the problem. In…

Computer Vision and Pattern Recognition · Computer Science 2026-05-18 Naama Pearl , Stefano Esposito , Haofei Xu , Amit Peleg , Patricia Gschossmann , Lorenzo Porzi , Peter Kontschieder , Gerard Pons-Moll , Andreas Geiger

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

Recent advancements in 3D Gaussian Splatting have enhanced efficient and high-quality novel view synthesis. However, representing scenes requires a large number of Gaussian points, leading to high storage demands and limiting practical…

Computer Vision and Pattern Recognition · Computer Science 2025-09-17 Liheng Zhang , Weihao Yu , Zubo Lu , Haozhi Gu , Jin Huang

Hybrid-capture novel view synthesis combines images at substantially different camera distances (e.g., aerial drone and ground-level views). Standard 3D Gaussian Splatting (3DGS), trained for 30K iterations with one rendered view per…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Sungjun Cho

Recent advancements in dynamic 3D scene reconstruction have shown promising results, enabling high-fidelity 3D novel view synthesis with improved temporal consistency. Among these, 4D Gaussian Splatting (4DGS) has emerged as an appealing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Seungjun Oh , Younggeun Lee , Hyejin Jeon , Eunbyung Park

3D Gaussian Splatting (3DGS) techniques have recently enabled high-quality 3D scene reconstruction and real-time novel view synthesis. These approaches, however, are limited by the pinhole camera model and lack effective modeling of defocus…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Yujie Wang , Praneeth Chakravarthula , Baoquan Chen

3D Gaussian Splatting (3DGS) has demonstrated its potential in reconstructing scenes from unposed images. However, optimization-based 3DGS methods struggle with sparse views due to limited prior knowledge. Meanwhile, feed-forward Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Chong Cheng , Yu Hu , Sicheng Yu , Beizhen Zhao , Zijian Wang , Hao Wang

3D Gaussian Splatting (3DGS) has demonstrated impressive novel view synthesis results while advancing real-time rendering performance. However, it relies heavily on the quality of the initial point cloud, resulting in blurring and…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Zheng Zhang , Wenbo Hu , Yixing Lao , Tong He , Hengshuang Zhao

In the rapidly evolving field of 3D reconstruction, 3D Gaussian Splatting (3DGS) and 2D Gaussian Splatting (2DGS) represent significant advancements. Although 2DGS compresses 3D Gaussian primitives into 2D Gaussian surfels to effectively…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Zhuoxiao Li , Shanliang Yao , Yijie Chu , Angel F. Garcia-Fernandez , Yong Yue , Eng Gee Lim , Xiaohui Zhu

Recently, the integration of the efficient feed-forward scheme into 3D Gaussian Splatting (3DGS) has been actively explored. However, most existing methods focus on sparse view reconstruction of small regions and cannot produce eligible…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Yunsong Wang , Tianxin Huang , Hanlin Chen , Gim Hee Lee