English
Related papers

Related papers: TopoGaussian: Inferring Internal Topology Structur…

200 papers

In this paper, we propose an end-to-end transcoding pipeline, to create 3D Gaussian splatting (3DGS) models from existing 3D plenoptic point cloud or mesh models, when the original multi-view images of the captured 3D object or scene are…

Image and Video Processing · Electrical Eng. & Systems 2026-05-21 Maja Krivokuća , Riad Bendouro , Neus Sabater

Reconstructing a 3D scene from images is challenging due to the different ways light interacts with surfaces depending on the viewer's position and the surface's material. In classical computer graphics, materials can be classified as…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Mateusz Nowak , Wojciech Jarosz , Peter Chin

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

3D Gaussian splatting (3DGS) has demonstrated exceptional performance in image-based 3D reconstruction and real-time rendering. However, regions with complex textures require numerous Gaussians to capture significant color variations…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Binxiao Huang , Zhihao Li , Shiyong Liu , Xiao Tang , Jiajun Tang , Jiaqi Lin , Yuxin Cheng , Zhenyu Chen , Xiaofei Wu , Ngai Wong

Recent advances in Gaussian Splatting have significantly advanced the field, achieving both panoptic and interactive segmentation of 3D scenes. However, existing methodologies often overlook the critical need for reconstructing specified…

Computer Vision and Pattern Recognition · Computer Science 2024-12-16 Liang Zhao , Zehan Bao , Yi Xie , Hong Chen , Yaohui Chen , Weifu Li

Three-dimensional Gaussian Splatting (3DGS) has recently emerged as an efficient representation for novel-view synthesis, achieving impressive visual quality. However, in scenes dominated by large and low-texture regions, common in indoor…

Computer Vision and Pattern Recognition · Computer Science 2025-10-29 Xirui Jin , Renbiao Jin , Boying Li , Danping Zou , Wenxian Yu

Physical simulation predicts future states of objects based on material properties and external loads, enabling blueprints for both Industry and Engineering to conduct risk management. Current 3D reconstruction-based simulators typically…

Machine Learning · Computer Science 2026-02-20 Yicheng Cao , Zhuo Huang , Yu Yao , Yiming Ying , Daoyi Dong , Tongliang Liu

Topology-consistent dynamic model sequences are essential for applications such as animation and model editing. However, existing 4D reconstruction methods face challenges in generating high-quality topology-consistent meshes. To address…

Graphics · Computer Science 2025-12-02 Hanzhi Guo , Dongdong Weng , Mo Su , Yixiao Chen , Xiaonuo Dongye , Chenyu Xu

We present a new, fast and flexible pipeline for indoor scene synthesis that is based on deep convolutional generative models. Our method operates on a top-down image-based representation, and inserts objects iteratively into the scene by…

Computer Vision and Pattern Recognition · Computer Science 2018-12-03 Daniel Ritchie , Kai Wang , Yu-an Lin

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

3D Gaussian Splatting (3DGS) has emerged as a powerful technique for generating photorealistic renderings of a scene in real-time. However, the volumetric nature of 3DGS limits its ability to accurately capture surface geometry. To address…

Computer Vision and Pattern Recognition · Computer Science 2026-05-04 Prajwal Gupta C. R. , Divyam Sheth , Jinjoo Ha , Mirela Ostrek , Justus Thies

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

Understanding 3D scenes is pivotal for autonomous driving, robotics, and augmented reality. Recent semantic Gaussian Splatting approaches leverage large-scale 2D vision models to project 2D semantic features onto 3D scenes. However, they…

Computer Vision and Pattern Recognition · Computer Science 2025-10-22 Tianyu Huang , Runnan Chen , Dongting Hu , Fengming Huang , Mingming Gong , Tongliang Liu

Virtual representations of physical critical infrastructures, such as water or energy plants, are used for simulations and digital twins to ensure resilience and continuity of their services. These models usually require 3D point clouds…

Computer Vision and Pattern Recognition · Computer Science 2026-04-29 Mike Diessner , Yannick E. Tarant

Gaussian Splatting (GS) has emerged as a crucial technique for representing discrete volumetric radiance fields. It leverages unique parametrization to mitigate computational demands in scene optimization. This work introduces…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Tianqi Shen , Shaohua Liu , Jiaqi Feng , Ziye Ma , Ning An

Despite recent successes in novel view synthesis using 3D Gaussian Splatting (3DGS), modeling scenes with sparse inputs remains a challenge. In this work, we address two critical yet overlooked issues in real-world sparse-input modeling:…

Computer Vision and Pattern Recognition · Computer Science 2025-03-10 Yingji Zhong , Zhihao Li , Dave Zhenyu Chen , Lanqing Hong , Dan Xu

We introduce ShapeGaussian, a high-fidelity, template-free method for 4D human reconstruction from casual monocular videos. Generic reconstruction methods lacking robust vision priors, such as 4DGS, struggle to capture high-deformation…

Computer Vision and Pattern Recognition · Computer Science 2026-02-06 Zhenxiao Liang , Ning Zhang , Youbao Tang , Ruei-Sung Lin , Qixing Huang , Peng Chang , Jing Xiao

Transparent and specular objects are frequently encountered in daily life, factories, and laboratories. However, due to the unique optical properties, the depth information on these objects is usually incomplete and inaccurate, which poses…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Yizhe Liu , Tong Jia , Da Cai , Hao Wang , Dongyue Chen

Minimally invasive surgery (MIS) requires high-fidelity, real-time visual feedback of dynamic and low-texture surgical scenes. To address these requirements, we introduce FeatureEndo-4DGS (FE-4DGS), the first real time pipeline leveraging…

Computer Vision and Pattern Recognition · Computer Science 2025-11-14 Kai Li , Junhao Wang , William Han , Ding Zhao

Open-vocabulary panoptic reconstruction is a challenging task for simultaneous scene reconstruction and understanding. Recently, methods have been proposed for 3D scene understanding based on Gaussian splatting. However, these methods are…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Yuxuan Xie , Xuan Yu , Changjian Jiang , Sitong Mao , Shunbo Zhou , Rui Fan , Rong Xiong , Yue Wang