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Related papers: Geometry-Consistent 4D Gaussian Splatting for Spar…

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This paper addresses the problem of dynamic scene surface reconstruction using Gaussian Splatting (GS), aiming to recover temporally consistent geometry. While existing GS-based dynamic surface reconstruction methods can yield superior…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Renjie Wu , Hongdong Li , Jose M. Alvarez , Miaomiao Liu

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

Using accurate depth priors in 3D Gaussian Splatting helps mitigate artifacts caused by sparse training data and textureless surfaces. However, acquiring accurate depth maps requires specialized acquisition systems. Foundation monocular…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Wenhui Xiao , Ethan Goan , Rodrigo Santa Cruz , David Ahmedt-Aristizabal , Olivier Salvado , Clinton Fookes , Leo Lebrat

3D Gaussian Splatting (3DGS) has shown remarkable success in synthesizing novel views given multiple views of a static scene. Yet, 3DGS faces challenges when applied to dynamic scenes because 3D Gaussian parameters need to be updated per…

Graphics · Computer Science 2024-07-08 Kai Katsumata , Duc Minh Vo , Hideki Nakayama

3D Gaussian Splatting (3DGS) has shown remarkable performance in novel view synthesis. However, its rendering quality deteriorates with sparse inphut views, leading to distorted content and reduced details. This limitation hinders its…

Computer Vision and Pattern Recognition · Computer Science 2025-01-22 Zongqi He , Zhe Xiao , Kin-Chung Chan , Yushen Zuo , Jun Xiao , Kin-Man Lam

The reconstruction of dynamic 3D scenes using 3D Gaussian Splatting has shown significant promise. A key challenge, however, remains in modeling realistic motion, as most methods fail to align the motion of Gaussians with real-world…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Junoh Lee , Junmyeong Lee , Yeon-Ji Song , Inhwan Bae , Jisu Shin , Hae-Gon Jeon , Jin-Hwa Kim

This letter introduces a novel framework for dense Visual Simultaneous Localization and Mapping (VSLAM) based on Gaussian Splatting. Recently, SLAM based on Gaussian Splatting has shown promising results. However, in monocular scenarios,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-11 Pengcheng Zhu , Yaoming Zhuang , Baoquan Chen , Li Li , Chengdong Wu , Zhanlin Liu

3D Gaussian Splatting has shown fast and high-quality rendering results in static scenes by leveraging dense 3D prior and explicit representations. Unfortunately, the benefits of the prior and representation do not involve novel view…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Junoh Lee , Chang-Yeon Won , Hyunjun Jung , Inhwan Bae , Hae-Gon Jeon

Gaussian splatting has become a popular representation for novel-view synthesis, exhibiting clear strengths in efficiency, photometric quality, and compositional edibility. Following its success, many works have extended Gaussians to 4D,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Colton Stearns , Adam Harley , Mikaela Uy , Florian Dubost , Federico Tombari , Gordon Wetzstein , Leonidas Guibas

Recent advances in 4D Gaussian Splatting (4DGS) editing still face challenges with view, temporal, and non-editing region consistency, as well as with handling complex text instructions. To address these issues, we propose 4DGS-Craft, a…

Computer Vision and Pattern Recognition · Computer Science 2025-10-03 Lei Liu , Can Wang , Zhenghao Chen , Dong Xu

3D Gaussian Splatting (3DGS) has emerged as a state-of-the-art method for novel view synthesis. However, its performance heavily relies on dense, high-quality input imagery, an assumption that is often violated in real-world applications,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Zhankuo Xu , Chaoran Feng , Yingtao Li , Jianbin Zhao , Jiashu Yang , Wangbo Yu , Li Yuan , Yonghong Tian

The advent of 3D Gaussian Splatting (3D-GS) techniques and their dynamic scene modeling variants, 4D-GS, offers promising prospects for real-time rendering of dynamic surgical scenarios. However, the prerequisite for modeling dynamic scenes…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Hengyu Liu , Yifan Liu , Chenxin Li , Wuyang Li , Yixuan Yuan

We present GP-4DGS, a novel framework that integrates Gaussian Processes (GPs) into 4D Gaussian Splatting (4DGS) for principled probabilistic modeling of dynamic scenes. While existing 4DGS methods focus on deterministic reconstruction,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Mijeong Kim , Jungtaek Kim , Bohyung Han

4D millimeter-wave radar is a promising sensing modality for autonomous driving, yet effective 3D object detection from 4D radar and monocular images remains challenging. Existing fusion approaches either rely on instance proposals lacking…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Xiaokai Bai , Chenxu Zhou , Lianqing Zheng , Si-Yuan Cao , Jianan Liu , Xiaohan Zhang , Yiming Li , Zhengzhuang Zhang , Hui-liang Shen

In-the-wild photo collections often contain limited volumes of imagery and exhibit multiple appearances, e.g., taken at different times of day or seasons, posing significant challenges to scene reconstruction and novel view synthesis.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-27 Deming Li , Kaiwen Jiang , Yutao Tang , Ravi Ramamoorthi , Rama Chellappa , Cheng Peng

3D Gaussian splatting (3DGS) is an innovative rendering technique that surpasses the neural radiance field (NeRF) in both rendering speed and visual quality by leveraging an explicit 3D scene representation. Existing 3DGS approaches require…

Computer Vision and Pattern Recognition · Computer Science 2025-06-13 Lintao Xiang , Hongpei Zheng , Yating Huang , Qijun Yang , Hujun Yin

4D content generation has achieved remarkable progress recently. However, existing methods suffer from long optimization times, a lack of motion controllability, and a low quality of details. In this paper, we introduce DreamGaussian4D…

Computer Vision and Pattern Recognition · Computer Science 2024-06-11 Jiawei Ren , Liang Pan , Jiaxiang Tang , Chi Zhang , Ang Cao , Gang Zeng , Ziwei Liu

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

Dynamic and static components in scenes often exhibit distinct properties, yet most 4D reconstruction methods treat them indiscriminately, leading to suboptimal performance in both cases. This work introduces SDD-4DGS, the first framework…

Computer Vision and Pattern Recognition · Computer Science 2025-03-13 Dai Sun , Huhao Guan , Kun Zhang , Xike Xie , S. Kevin Zhou

In the realm of robot-assisted minimally invasive surgery, dynamic scene reconstruction can significantly enhance downstream tasks and improve surgical outcomes. Neural Radiance Fields (NeRF)-based methods have recently risen to prominence…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Yiming Huang , Beilei Cui , Long Bai , Ziqi Guo , Mengya Xu , Mobarakol Islam , Hongliang Ren