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Related papers: Decoupling Motion and Geometry in 4D Gaussian Spla…

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We propose Quadratic Gaussian Splatting (QGS), a novel representation that replaces static primitives with deformable quadric surfaces (e.g., ellipse, paraboloids) to capture intricate geometry. Unlike prior works that rely on Euclidean…

Computer Vision and Pattern Recognition · Computer Science 2025-08-19 Ziyu Zhang , Binbin Huang , Hanqing Jiang , Liyang Zhou , Xiaojun Xiang , Shunhan Shen

We propose GauS-SLAM, a dense RGB-D SLAM system that leverages 2D Gaussian surfels to achieve robust tracking and high-fidelity mapping. Our investigations reveal that Gaussian-based scene representations exhibit geometry distortion under…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Yongxin Su , Lin Chen , Kaiting Zhang , Zhongliang Zhao , Chenfeng Hou , Ziping Yu

Modeling dynamic, large-scale urban scenes is challenging due to their highly intricate geometric structures and unconstrained dynamics in both space and time. Prior methods often employ high-level architectural priors, separating static…

Computer Vision and Pattern Recognition · Computer Science 2025-08-26 Yurui Chen , Chun Gu , Junzhe Jiang , Xiatian Zhu , Li Zhang

High-fidelity 3D video reconstruction is essential for enabling real-time rendering of dynamic scenes with realistic motion in virtual and augmented reality (VR/AR). The deformation field paradigm of 3D Gaussian splatting has achieved…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 Zhenyang Li , Xiaoyang Bai , Tongchen Zhang , Pengfei Shen , Weiwei Xu , Yifan Peng

Photorealistic 3D reconstruction of street scenes is a critical technique for developing real-world simulators for autonomous driving. Despite the efficacy of Neural Radiance Fields (NeRF) for driving scenes, 3D Gaussian Splatting (3DGS)…

Computer Vision and Pattern Recognition · Computer Science 2024-05-31 Nan Huang , Xiaobao Wei , Wenzhao Zheng , Pengju An , Ming Lu , Wei Zhan , Masayoshi Tomizuka , Kurt Keutzer , Shanghang Zhang

High-dynamic scene reconstruction aims to represent static background with rigid spatial features and dynamic objects with deformed continuous spatiotemporal features. Typically, existing methods adopt unified representation model (e.g.,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Hanyu Zhou , Haonan Wang , Haoyue Liu , Yuxing Duan , Luxin Yan , Gim Hee Lee

The underwater 3D scene reconstruction is a challenging, yet interesting problem with applications ranging from naval robots to VR experiences. The problem was successfully tackled by fully volumetric NeRF-based methods which can model both…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Huapeng Li , Wenxuan Song , Tianao Xu , Alexandre Elsig , Jonas Kulhanek

While 3D Gaussian Splatting (3DGS) has revolutionized real-time photorealistic view synthesis, its fundamental reliance on symmetric Gaussian distributions introduces visual artifacts that hinder accurate spatial data exploration.…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Beizhen Zhao , Yifan Zhou , Gaochao Song , Ziran Yin , Hao Wang

Retrospective novel view synthesis (NVS) of dynamic scenes is fundamental to applications such as sports. Recent dynamic 3D Gaussian Splatting (3DGS) approaches introduce temporally coupled formulations to enforce motion coherence across…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Yunxiao Zhang , Suryansh Kumar

Deformable Gaussian Splatting (GS) accomplishes photorealistic dynamic 3-D reconstruction from dense multi-view video (MVV) by learning to deform a canonical GS representation. However, in filmmaking, tight budgets can result in sparse…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Adrian Azzarelli , Nantheera Anantrasirichai , David R Bull

3D Gaussian splatting (3DGS) has shown promising results in image rendering and surface reconstruction. However, its potential in volumetric reconstruction tasks, such as X-ray computed tomography, remains under-explored. This paper…

Image and Video Processing · Electrical Eng. & Systems 2024-10-29 Ruyi Zha , Tao Jun Lin , Yuanhao Cai , Jiwen Cao , Yanhao Zhang , Hongdong Li

Implicit Neural Representations (INRs) employ neural networks to approximate discrete data as continuous functions. In the context of video data, such models can be utilized to transform the coordinates of pixel locations along with frame…

Computer Vision and Pattern Recognition · Computer Science 2026-02-19 Weronika Smolak-Dyżewska , Dawid Malarz , Kornel Howil , Jan Kaczmarczyk , Marcin Mazur , Przemysław Spurek

Recently, Gaussian Splatting, a method that represents a 3D scene as a collection of Gaussian distributions, has gained significant attention in addressing the task of novel view synthesis. In this paper, we highlight a fundamental…

Computer Vision and Pattern Recognition · Computer Science 2024-10-31 Haoxuan Qu , Zhuoling Li , Hossein Rahmani , Yujun Cai , Jun Liu

Branches swaying in the breeze, flags rippling in the wind, and boats rocking on the water all show how aerodynamics shape natural motion -- an effect crucial for realism in vision and graphics. In this paper, we present Gaussian Swaying, a…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Hongru Yan , Xiang Zhang , Zeyuan Chen , Fangyin Wei , Zhuowen Tu

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

Recent advances in Gaussian Splatting have enabled fast, high-fidelity 3D scene generation, yet these methods remain purely visual and lack an understanding of how shapes behave in the physical world. We introduce Physics-Guided 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Zachary Lee , Maxwell Jacobson , Yexiang Xue

Feedforward Gaussian Splatting has recently emerged as an efficient paradigm for 4D reconstruction in autonomous driving. However, in unstructured off-road scenes, its performance degrades due to high-frequency geometry, ego-motion jitter,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Shuo Wang , Jilin Mei , Fuyang Liu , Wenfei Guan , Fanjie Kong , Zhihua Zhao , Shuai Wang , Chen Min , Yu Hu

Reconstructing dynamic 4D scenes from monocular videos is a fundamental yet challenging task. While recent 3D foundation models provide strong geometric priors, their performance significantly degrades in dynamic environments. This…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Ying Zang , Xuanyi Liu , Yidong Han , Deyi Ji , Chaotao Ding , Yuanqi Hu , Qi Zhu , Xuanfu Li , Jin Ma , Lingyun Sun , Tianrun Chen , Lanyun Zhu

Recently, Gaussian splatting has received more and more attention in the field of static scene rendering. Due to the low computational overhead and inherent flexibility of explicit representations, plane-based explicit methods are popular…

Computer Vision and Pattern Recognition · Computer Science 2024-12-30 Jiawei Xu , Zexin Fan , Jian Yang , Jin Xie

Reconstructing 3D fluid velocity fields from sparse 2D video observations is a highly ill-posed inverse problem, demanding both transport consistency with observed motion and physical validity under fluid laws. Existing methods typically…

Graphics · Computer Science 2026-05-12 Ningxiao Tao , Baoquan Chen , Mengyu Chu