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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

Synthesizing novel views of large-scale scenes from unconstrained in-the-wild images is an important but challenging task in computer vision. Existing methods, which optimize per-image appearance and transient occlusion through implicit…

Computer Vision and Pattern Recognition · Computer Science 2026-02-02 Yiqing Li , Xuan Wang , Jiawei Wu , Yikun Ma , Zhi Jin

We present Real-time Gaussian SLAM (RTG-SLAM), a real-time 3D reconstruction system with an RGBD camera for large-scale environments using Gaussian splatting. The system features a compact Gaussian representation and a highly efficient…

Computer Vision and Pattern Recognition · Computer Science 2024-05-10 Zhexi Peng , Tianjia Shao , Yong Liu , Jingke Zhou , Yin Yang , Jingdong Wang , Kun Zhou

Recent advancements in photo-realistic novel view synthesis have been significantly driven by Gaussian Splatting (3DGS). Nevertheless, the explicit nature of 3DGS data entails considerable storage requirements, highlighting a pressing need…

Computer Vision and Pattern Recognition · Computer Science 2024-11-12 Minye Wu , Tinne Tuytelaars

3D Gaussian Splatting algorithms excel in novel view rendering applications and have been adapted to extend the capabilities of traditional SLAM systems. However, current Gaussian Splatting SLAM methods, designed mainly for hand-held RGB or…

Robotics · Computer Science 2024-10-01 Zunjie Zhu , Youxu Fang , Xin Li , Chengang Yan , Feng Xu , Chau Yuen , Yanyan Li

3D Gaussian Splatting (3DGS) has demonstrated superior quality in modeling 3D objects and scenes. However, generating 3DGS remains challenging due to their discrete, unstructured, and permutation-invariant nature. In this work, we present a…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Aashish Rai , Dilin Wang , Mihir Jain , Nikolaos Sarafianos , Kefan Chen , Srinath Sridhar , Aayush Prakash

This work addresses the problem of real-time rendering of photorealistic human body avatars learned from multi-view videos. While the classical approaches to model and render virtual humans generally use a textured mesh, recent research has…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Arthur Moreau , Jifei Song , Helisa Dhamo , Richard Shaw , Yiren Zhou , Eduardo Pérez-Pellitero

While Implicit Neural Representations (INRs) have demonstrated significant success in image representation, they are often hindered by large training memory and slow decoding speed. Recently, Gaussian Splatting (GS) has emerged as a…

Computer Vision and Pattern Recognition · Computer Science 2025-02-14 Lingting Zhu , Guying Lin , Jinnan Chen , Xinjie Zhang , Zhenchao Jin , Zhao Wang , Lequan Yu

3D Gaussian Splatting (3D-GS) enables efficient novel view synthesis, but treats all frequencies uniformly, making it difficult to separate coarse structure from fine detail. Recent works have started to exploit frequency signals, but lack…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Yishai Lavi , Leo Segre , Shai Avidan

Novel view synthesis for underwater scene reconstruction presents unique challenges due to complex light-media interactions. Optical scattering and absorption in water body bring inhomogeneous medium attenuation interference that disrupts…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Jieyu Yuan , Yujun Li , Yuanlin Zhang , Chunle Guo , Xiongxin Tang , Ruixing Wang , Chongyi Li

Recent work has shown that 3D Gaussian-based SLAM enables high-quality reconstruction, accurate pose estimation, and real-time rendering of scenes. However, these approaches are built on a tremendous number of redundant 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Tianchen Deng , Chang Nie , Shuhong Liu , Wenhua Wu , Jianfei Yang , Shenghai Yuan , Jiuming Liu , Danwei Wang , Hesheng Wang

Dynamic reconstruction of deformable tissues in endoscopic video is a key technology for robot-assisted surgery. Recent reconstruction methods based on neural radiance fields (NeRFs) have achieved remarkable results in the reconstruction of…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 Weixing Xie , Junfeng Yao , Xianpeng Cao , Qiqin Lin , Zerui Tang , Xiao Dong , Xiaohu Guo

Novel view synthesis for dynamic scenes is still a challenging problem in computer vision and graphics. Recently, Gaussian splatting has emerged as a robust technique to represent static scenes and enable high-quality and real-time novel…

Computer Vision and Pattern Recognition · Computer Science 2024-04-15 Yi-Hua Huang , Yang-Tian Sun , Ziyi Yang , Xiaoyang Lyu , Yan-Pei Cao , Xiaojuan Qi

3D Gaussian Splatting (3DGS) has recently emerged as a pioneering approach in explicit scene rendering and computer graphics. Unlike traditional neural radiance field (NeRF) methods, which typically rely on implicit, coordinate-based models…

We propose a method to enhance 3D Gaussian Splatting (3DGS)~\cite{Kerbl2023}, addressing challenges in initialization, optimization, and density control. Gaussian Splatting is an alternative for rendering realistic images while supporting…

Computer Vision and Pattern Recognition · Computer Science 2025-07-02 Xingjun Wang , Lianlei Shan

Holistic understanding of urban scenes based on RGB images is a challenging yet important problem. It encompasses understanding both the geometry and appearance to enable novel view synthesis, parsing semantic labels, and tracking moving…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Hongyu Zhou , Jiahao Shao , Lu Xu , Dongfeng Bai , Weichao Qiu , Bingbing Liu , Yue Wang , Andreas Geiger , Yiyi Liao

While 3D Gaussian splatting (3DGS) offers explicit and efficient scene representations for cone-beam computed tomography reconstruction, conventional photometric optimization inherently suffers from spectral bias under ultra sparse-view…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Jian Lin , Jiancheng Fang , Shaoyu Wang , Changan Lai , Yikun Zhang , Yang Chen , Qiegen Liu

3D Gaussian Splatting (3DGS) proposes an efficient solution for novel view synthesis. Its framework provides fast and high-fidelity rendering. Although less complex than other solutions such as Neural Radiance Fields (NeRF), there are still…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Stéphane Pateux , Matthieu Gendrin , Luce Morin , Théo Ladune , Xiaoran Jiang

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

2D Gaussian Splatting has recently emerged as a significant method in 3D reconstruction, enabling novel view synthesis and geometry reconstruction simultaneously. While the well-known Gaussian kernel is broadly used, its lack of anisotropy…

Computer Vision and Pattern Recognition · Computer Science 2024-09-02 Ruihan Yu , Tianyu Huang , Jingwang Ling , Feng Xu