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Recently, Gaussian Splatting methods have emerged as a desirable substitute for prior Radiance Field methods for novel-view synthesis of scenes captured with multi-view images or videos. In this work, we propose a novel extension to 4D…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Karly Hou , Wanhua Li , Hanspeter Pfister

3D Gaussian Splatting (3DGS) has emerged as a powerful and efficient 3D representation for novel view synthesis. This paper extends 3DGS capabilities to inpainting, where masked objects in a scene are replaced with new contents that blend…

Computer Vision and Pattern Recognition · Computer Science 2025-04-28 Mingxuan Cui , Qing Guo , Yuyi Wang , Hongkai Yu , Di Lin , Qin Zou , Ming-Ming Cheng , Xi Li

Since its introduction, 3D Gaussian Splatting (3DGS) has rapidly transformed the landscape of 3D scene representations, inspiring an extensive body of associated research. Follow-up work includes analyses and contributions that enhance the…

Computer Vision and Pattern Recognition · Computer Science 2025-10-31 Bernhard Kerbl

Implicit neural representation methods have shown impressive advancements in learning 3D scenes from unstructured in-the-wild photo collections but are still limited by the large computational cost of volumetric rendering. More recently, 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 Hiba Dahmani , Moussab Bennehar , Nathan Piasco , Luis Roldao , Dzmitry Tsishkou

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

Dynamic scene rendering opens new avenues in autonomous driving by enabling closed-loop simulations with photorealistic data, which is crucial for validating end-to-end algorithms. However, the complex and highly dynamic nature of traffic…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Rui Song , Chenwei Liang , Yan Xia , Walter Zimmer , Hu Cao , Holger Caesar , Andreas Festag , Alois Knoll

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

The shape of an object is an important characteristic for many vision problems such as segmentation, detection and tracking. Being independent of appearance, it is possible to generalize to a large range of objects from only small amounts…

Machine Learning · Statistics 2018-12-14 Alessandro Di Martino , Erik Bodin , Carl Henrik Ek , Neill D. F. Campbell

3D Gaussian Splatting (3DGS) has garnered significant attention due to its superior scene representation fidelity and real-time rendering performance, especially for dynamic 3D scene reconstruction (\textit{i.e.}, 4D reconstruction).…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Henan Wang , Hanxin Zhu , Xinliang Gong , Tianyu He , Xin Li , Zhibo Chen

3D Gaussian Splatting (3DGS) has demonstrated impressive novel view synthesis performance. While conventional methods require per-scene optimization, more recently several feed-forward methods have been proposed to generate pixel-aligned…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Shengjun Zhang , Xin Fei , Fangfu Liu , Haixu Song , Yueqi Duan

Gaussian Splatting (GS) is a novel, state-of-the-art technique for rendering points in a 3D scene by approximating their contribution to image pixels through Gaussian distributions, warranting fast training and real-time rendering. The main…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Joanna Waczyńska , Piotr Borycki , Sławomir Tadeja , Jacek Tabor , Przemysław Spurek

3D Gaussian splatting models, as a novel explicit 3D representation, have been applied in many domains recently, such as explicit geometric editing and geometry generation. Progress has been rapid. However, due to their mixed scales and…

Graphics · Computer Science 2024-03-15 Qiyuan Feng , Gengchen Cao , Haoxiang Chen , Tai-Jiang Mu , Ralph R. Martin , Shi-Min Hu

Sparse Multi-view Images can be Learned to predict explicit radiance fields via Generalizable Gaussian Splatting approaches, which can achieve wider application prospects in real-life when ground-truth camera parameters are not required as…

Computer Vision and Pattern Recognition · Computer Science 2024-11-28 Yanyan Li , Yixin Fang , Federico Tombari , Gim Hee Lee

Gaussian Splatting has rapidly emerged as a transformative technique for real-time 3D scene representation, offering a highly efficient and expressive alternative to Neural Radiance Fields (NeRF). Its ability to render complex scenes with…

Graphics · Computer Science 2025-08-20 Mahmoud Chick Zaouali , Todd Charter , Yehor Karpichev , Brandon Haworth , Homayoun Najjaran

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

We introduce a general framework for undirected graphical models. It generalizes Gaussian graphical models to a wide range of continuous, discrete, and combinations of different types of data. The models in the framework, called exponential…

Statistics Theory · Mathematics 2019-06-18 Rui Zhuang , Noah Simon , Johannes Lederer

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

Robust and realistic rendering for large-scale road scenes is essential in autonomous driving simulation. Recently, 3D Gaussian Splatting (3D-GS) has made groundbreaking progress in neural rendering, but the general fidelity of large-scale…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Saining Zhang , Baijun Ye , Xiaoxue Chen , Yuantao Chen , Zongzheng Zhang , Cheng Peng , Yongliang Shi , Hao Zhao

Image inpainting is a fundamental task in computer vision, aiming to restore missing or corrupted regions in images realistically. While recent deep learning approaches have significantly advanced the state-of-the-art, challenges remain in…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Jacob Fein-Ashley , Benjamin Fein-Ashley

3D Gaussian Splatting (3DGS) enables real-time, photorealistic novel view synthesis, making it a highly attractive representation for model-based video tracking. However, leveraging the differentiability of the 3DGS renderer "in the wild"…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Avigail Cohen Rimon , Amir Mann , Mirela Ben Chen , Or Litany