The Hessigheim 3D (H3D) benchmark on semantic segmentation of high-resolution 3D point clouds and textured meshes from UAV LiDAR and Multi-View-Stereo-Reference-Cited by-同舟云学术

The Hessigheim 3D (H3D) benchmark on semantic segmentation of high-resolution 3D point clouds and textured meshes from UAV LiDAR and Multi-View-Stereo

Published:2021-10 Issue: Volume:1 Page:100001
ISSN:2667-3932
Container-title:ISPRS Open Journal of Photogrammetry and Remote Sensing
language:en
Short-container-title:ISPRS Open Journal of Photogrammetry and Remote Sensing

Author:

Kölle Michael,Laupheimer Dominik,Schmohl Stefan^ORCID,Haala Norbert,Rottensteiner Franz^ORCID,Wegner Jan Dirk,Ledoux Hugo^ORCID

Publisher

Elsevier BV

Reference46 articles.

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5. nuscenes: a multimodal dataset for autonomous driving;Caesar,2020

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