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Related papers: PhyCAGE: Physically Plausible Compositional 3D Ass…

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We present the first evaluation of 3D Gaussian Splatting methods on real fisheye imagery with fields of view above 180\textdegree{}. Our study evaluates Fisheye-GS \cite{liao2024fisheyegslightweightextensiblegaussian} and 3DGUT…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Ulas Gunes , Matias Turkulainen , Mikhail Silaev , Juho Kannala , Esa Rahtu

We present DrivingGaussian, an efficient and effective framework for surrounding dynamic autonomous driving scenes. For complex scenes with moving objects, we first sequentially and progressively model the static background of the entire…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Xiaoyu Zhou , Zhiwei Lin , Xiaojun Shan , Yongtao Wang , Deqing Sun , Ming-Hsuan Yang

3D Gaussian Splatting (3DGS) is a leading 3D scene reconstruction method, obtaining high-quality reconstruction with real-time rendering runtime performance. The main idea behind 3DGS is to represent the scene as a collection of 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Rajaei Khatib , Raja Giryes

Dynamic Gaussian splatting has led to impressive scene reconstruction and image synthesis advances in novel views. Existing methods, however, heavily rely on pre-computed poses and Gaussian initialization by Structure from Motion (SfM)…

Computer Vision and Pattern Recognition · Computer Science 2024-06-27 Hao Li , Jingfeng Li , Dingwen Zhang , Chenming Wu , Jieqi Shi , Chen Zhao , Haocheng Feng , Errui Ding , Jingdong Wang , Junwei Han

In this paper, we aim to model 3D scene geometry, appearance, and the underlying physics purely from multi-view videos. By applying various governing PDEs as PINN losses or incorporating physics simulation into neural networks, existing…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Jinxi Li , Ziyang Song , Siyuan Zhou , Bo Yang

We propose WildSplatter, a feed-forward 3D Gaussian Splatting (3DGS) model for unconstrained images with unknown camera parameters and varying lighting conditions. 3DGS is an effective scene representation that enables high-quality,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Yuki Fujimura , Takahiro Kushida , Kazuya Kitano , Takuya Funatomi , Yasuhiro Mukaigawa

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

This paper introduces a novel clothed human model that can be learned from multiview RGB videos, with a particular emphasis on recovering physically accurate body and cloth movements. Our method, Position Based Dynamic Gaussians (PBDyG),…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Shota Sasaki , Jane Wu , Ko Nishino

3D Gaussian Splatting (3DGS) has recently emerged as a state-of-the-art 3D reconstruction and rendering technique due to its high-quality results and fast training and rendering time. However, pixels covered by the same Gaussian are always…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Brian Chao , Hung-Yu Tseng , Lorenzo Porzi , Chen Gao , Tuotuo Li , Qinbo Li , Ayush Saraf , Jia-Bin Huang , Johannes Kopf , Gordon Wetzstein , Changil Kim

Recent advancements in 3D generation models have opened new possibilities for simulating dynamic 3D object movements and customizing behaviors, yet creating this content remains challenging. Current methods often require manual assignment…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Haoyu Zhao , Hao Wang , Xingyue Zhao , Hao Fei , Hongqiu Wang , Chengjiang Long , Hua Zou

3D Gaussian Splatting (3DGS) has significantly improved the efficiency and realism of three-dimensional scene visualization in several applications, ranging from robotics to eXtended Reality (XR). This work presents SAGE (Semantic-Driven…

Graphics · Computer Science 2025-03-24 Chiara Schiavo , Elena Camuffo , Leonardo Badia , Simone Milani

The increasing demand for augmented reality and robotics is driving the need for articulated object reconstruction with high scalability. However, existing settings for reconstructing from discrete articulation states or casual monocular…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Hang Dai , Hongwei Fan , Han Zhang , Duojin Wu , Jiyao Zhang , Hao Dong

Synthesizing novel views from in-the-wild monocular videos is challenging due to scene dynamics and the lack of multi-view cues. To address this, we propose SplineGS, a COLMAP-free dynamic 3D Gaussian Splatting (3DGS) framework for…

Computer Vision and Pattern Recognition · Computer Science 2024-12-19 Jongmin Park , Minh-Quan Viet Bui , Juan Luis Gonzalez Bello , Jaeho Moon , Jihyong Oh , Munchurl Kim

Interactable objects are ubiquitous in our daily lives. Recent advances in 3D generative models make it possible to automate the modeling of these objects, benefiting a range of applications from 3D printing to the creation of robot…

Computer Vision and Pattern Recognition · Computer Science 2025-02-05 Rundong Luo , Haoran Geng , Congyue Deng , Puhao Li , Zan Wang , Baoxiong Jia , Leonidas Guibas , Siyuan Huang

3D Gaussian Splatting (3DGS) has emerged as a powerful explicit representation enabling real-time, high-fidelity 3D reconstruction and novel view synthesis. However, its practical use is hindered by the massive memory and computational…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Seokhyun Youn , Soohyun Lee , Geonho Kim , Weeyoung Kwon , Sung-Ho Bae , Jihyong Oh

We address the challenge of generating 3D articulated objects in a controllable fashion. Currently, modeling articulated 3D objects is either achieved through laborious manual authoring, or using methods from prior work that are hard to…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Jiayi Liu , Hou In Ivan Tam , Ali Mahdavi-Amiri , Manolis Savva

3D Gaussian Splatting (3DGS) enhances 3D scene reconstruction through explicit representation and fast rendering, demonstrating potential benefits for various low-level vision tasks, including video compression. However, existing 3DGS-based…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Siyue Teng , Ge Gao , Duolikun Danier , Yuxuan Jiang , Fan Zhang , Thomas Davis , Zoe Liu , David Bull

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

With 3D Gaussian Splatting (3DGS) advancing real-time and high-fidelity rendering for novel view synthesis, storage requirements pose challenges for their widespread adoption. Although various compression techniques have been proposed,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-13 Yihang Chen , Qianyi Wu , Mengyao Li , Weiyao Lin , Mehrtash Harandi , Jianfei Cai

Neural image representations have emerged as a promising approach for encoding and rendering visual data. Combined with learning-based workflows, they demonstrate impressive trade-offs between visual fidelity and memory footprint. Existing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-08 Yunxiang Zhang , Bingxuan Li , Alexandr Kuznetsov , Akshay Jindal , Stavros Diolatzis , Kenneth Chen , Anton Sochenov , Anton Kaplanyan , Qi Sun
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