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hal.structure.identifierBiodiversité, Gènes & Communautés [BioGeCo]
hal.structure.identifierEcole Nationale Supérieure de Géologie [ENSG]
hal.structure.identifierIGN-France International [IGN FI]
dc.contributor.authorKALINICHEVA, Ekaterina
hal.structure.identifierEcole Nationale Supérieure de Géologie [ENSG]
hal.structure.identifierIGN-France International [IGN FI]
dc.contributor.authorLANDRIEU, Loic
hal.structure.identifierEcole Nationale Supérieure de Géologie [ENSG]
hal.structure.identifierIGN-France International [IGN FI]
dc.contributor.authorMALLET, Clement
hal.structure.identifierInstitut Polytechnique de Bordeaux [Bordeaux INP]
hal.structure.identifierEcole Nationale Supérieure de Géologie [ENSG]
hal.structure.identifierIGN-France International [IGN FI]
dc.contributor.authorCHEHATA, Nesrine
dc.date.conference2022-06-19
dc.description.abstractEnThe analysis of the multi-layer structure of wild forests is an important challenge of automated large-scale forestry. While modern aerial LiDARs offer geometric information across all vegetation layers, most datasets and methods focus only on the segmentation and reconstruction of the top of canopy. We release WildForest3D, which consists of 29 study plots and over 2000 individual trees across 47 000m 2 with dense 3D annotation, along with occupancy and height maps for 3 vegetation layers: ground vegetation, understory, and overstory. We propose a 3D deep network architecture predicting for the first time both 3D point-wise labels and high-resolution layer occupancy rasters simultaneously. This allows us to produce a precise estimation of the thickness of each vegetation layer as well as the corresponding watertight meshes, therefore meeting most forestry purposes. Both the dataset and the model are released in open access: https://github.com/ekalinicheva/multi_layer_vegetation.
dc.language.isoen
dc.publisherIEEE
dc.subject.enComputer vision
dc.subject.enSolid modeling
dc.subject.enThree-dimensional displays
dc.subject.enLaser radar
dc.subject.enAnnotations
dc.subject.enAtmospheric modeling
dc.subject.enTime series analysis
dc.typeCommunication dans un congrès
dc.identifier.doi10.1109/CVPRW56347.2022.00140
dc.subject.halSciences de l'environnement
dc.identifier.arxiv2204.11620
bordeaux.page1341-1350
bordeaux.countryUS
bordeaux.conference.cityNew Orleans
bordeaux.peerReviewedoui
hal.identifierhal-04071838
hal.version1
hal.invitednon
hal.proceedingsnon
hal.conference.end2022-06-20
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-04071838v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.spage=1341-1350&rft.epage=1341-1350&rft.au=KALINICHEVA,%20Ekaterina&LANDRIEU,%20Loic&MALLET,%20Clement&CHEHATA,%20Nesrine&rft.genre=unknown


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