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Papers 3D Surface Generation

“3D Surface Generation” 태그가 달린 논문 10편 · 필터 해제

MoReMouse: Monocular Reconstruction of Laboratory Mouse

2025-07-06 · Yuan Zhong, Jingxiang Sun, Liang An, Yebin Liu

Laboratory mice play a crucial role in biomedical research, yet accurate 3D mouse surface motion reconstruction remains challenging due to their complex non-rigid geometric deformations and textureless appearance. Moreov…

3D Reconstruction3D Surface GenerationMonocular Reconstruction

DoubleDiffusion: Combining Heat Diffusion with Denoising Diffusion for Texture Generation on 3D Meshes

2025-01-06 · Xuyang Wang, Ziang Cheng, Zhenyu Li, Jiayu Yang 외

This paper addresses the problem of generating textures for 3D mesh assets. Existing approaches often rely on image diffusion models to generate multi-view image observations, which are then transformed onto the mesh sur…

3D Surface GenerationGeometry-based operator learningLatent Diffusion Model for 3DTexture Synthesis

Satellite Sunroof: High-res Digital Surface Models and Roof Segmentation for Global Solar Mapping

2024-08-26 · Vishal Batchu, Alex Wilson, Betty Peng, Carl Elkin 외

The transition to renewable energy, particularly solar, is key to mitigating climate change. Google's Solar API aids this transition by estimating solar potential from aerial imagery, but its impact is constrained by geo…

3D Surface GenerationEarth ObservationInstance SegmentationSegmentation+2

Towards Automating the Retrospective Generation of BIM Models: A Unified Framework for 3D Semantic Reconstruction of the Built Environment

2024-06-03 · Ka Lung Cheung, Chi Chung Lee

The adoption of Building Information Modeling (BIM) is beneficial in construction projects. However, it faces challenges due to the lack of a unified and scalable framework for converting 3D model details into BIM. This …

3D Architecture3D Semantic Segmentation3D Surface GenerationExtracting Buildings In Remote Sensing Images+2

Vis2Mesh: Efficient Mesh Reconstruction from Unstructured Point Clouds of Large Scenes with Learned Virtual View Visibility

2021-08-18 · ICCV 2021 10 · Shuang Song, Zhaopeng Cui, Rongjun Qin

We present a novel framework for mesh reconstruction from unstructured point clouds by taking advantage of the learned visibility of the 3D points in the virtual views and traditional graph-cut based mesh generation. Spe…

3D Surface GenerationBinary ClassificationDepth CompletionVisibility Estimation from Point Cloud

Quality assessment of image matchers for DSM generation -- a comparative study based on UAV images

2021-08-18 · Rongjun Qin, Armin Gruen, Cive Fraser

Recently developed automatic dense image matching algorithms are now being implemented for DSM/DTM production, with their pixel-level surface generation capability offering the prospect of partially alleviating the need …

3D Surface Generation

GAMesh: Guided and Augmented Meshing for Deep Point Networks

2020-10-19 · Nitin Agarwal, M Gopi

We present a new meshing algorithm called guided and augmented meshing, GAMesh, which uses a mesh prior to generate a surface for the output points of a point network. By projecting the output points onto this prior and …

3D Reconstruction3D Shape Reconstruction3D Surface GenerationSingle-View 3D Reconstruction+1

3D-CODED : 3D Correspondences by Deep Deformation

2018-06-13 · Thibault Groueix, Matthew Fisher, Vladimir G. Kim, Bryan C. Russell 외

We present a new deep learning approach for matching deformable shapes by introducing {\it Shape Deformation Networks} which jointly encode 3D shapes and correspondences. This is achieved by factoring the surface represe…

3D Dense Shape Correspondence3D Human Pose Estimation3D Point Cloud Matching3D Surface Generation

A Papier-Mâché Approach to Learning 3D Surface Generation

2018-06-01 · CVPR 2018 6 · Thibault Groueix, Matthew Fisher, Vladimir G. Kim, Bryan C. Russell 외

We introduce a method for learning to generate the surface of 3D shapes. Our approach represents a 3D shape as a collection of parametric surface elements and, in contrast to methods generating voxel grids or point cloud…

3D Surface GenerationSuper-Resolution

AtlasNet: A Papier-Mâché Approach to Learning 3D Surface Generation

2018-02-15 · Thibault Groueix, Matthew Fisher, Vladimir G. Kim, Bryan C. Russell 외

We introduce a method for learning to generate the surface of 3D shapes. Our approach represents a 3D shape as a collection of parametric surface elements and, in contrast to methods generating voxel grids or point cloud…

3D Surface GenerationPoint Cloud CompletionSuper-Resolution
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