abstracts[] |
{'sha1': '4523b7b0444de3afa8f3b7410a8ce0b6dbc53aff', 'content': 'Automated semantic segmentation and object detection are of great importance\nin geospatial data analysis. However, supervised machine learning systems such\nas convolutional neural networks require large corpora of annotated training\ndata. Especially in the geospatial domain, such datasets are quite scarce.\nWithin this paper, we aim to alleviate this issue by introducing a new\nannotated 3D dataset that is unique in three ways: i) The dataset consists of\nboth an Unmanned Aerial Vehicle (UAV) laser scanning point cloud and a 3D\ntextured mesh. ii) The point cloud features a mean point density of about 800\npts/sqm and the oblique imagery used for 3D mesh texturing realizes a ground\nsampling distance of about 2-3 cm. This enables the identification of\nfine-grained structures and represents the state of the art in UAV-based\nmapping. iii) Both data modalities will be published for a total of three\nepochs allowing applications such as change detection. The dataset depicts the\nvillage of Hessigheim (Germany), henceforth referred to as H3D. It is designed\nto promote research in the field of 3D data analysis on one hand and to\nevaluate and rank existing and emerging approaches for semantic segmentation of\nboth data modalities on the other hand. Ultimately, we hope that H3D will\nbecome a widely used benchmark dataset in company with the well-established\nISPRS Vaihingen 3D Semantic Labeling Challenge benchmark (V3D). The dataset can\nbe downloaded from\nhttps://ifpwww.ifp.uni-stuttgart.de/benchmark/hessigheim/default.aspx.', 'mimetype': 'text/plain', 'lang': 'en'}
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contribs[] |
{'index': 0, 'creator_id': None, 'creator': None, 'raw_name': 'Michael Kölle', 'given_name': None, 'surname': None, 'role': 'author', 'raw_affiliation': None, 'extra': None}
{'index': 1, 'creator_id': None, 'creator': None, 'raw_name': 'Dominik Laupheimer', 'given_name': None, 'surname': None, 'role': 'author', 'raw_affiliation': None, 'extra': None}
{'index': 2, 'creator_id': None, 'creator': None, 'raw_name': 'Stefan Schmohl', 'given_name': None, 'surname': None, 'role': 'author', 'raw_affiliation': None, 'extra': None}
{'index': 3, 'creator_id': None, 'creator': None, 'raw_name': 'Norbert Haala', 'given_name': None, 'surname': None, 'role': 'author', 'raw_affiliation': None, 'extra': None}
{'index': 4, 'creator_id': None, 'creator': None, 'raw_name': 'Franz Rottensteiner', 'given_name': None, 'surname': None, 'role': 'author', 'raw_affiliation': None, 'extra': None}
{'index': 5, 'creator_id': None, 'creator': None, 'raw_name': 'Jan Dirk Wegner', 'given_name': None, 'surname': None, 'role': 'author', 'raw_affiliation': None, 'extra': None}
{'index': 6, 'creator_id': None, 'creator': None, 'raw_name': 'Hugo Ledoux', 'given_name': None, 'surname': None, 'role': 'author', 'raw_affiliation': None, 'extra': None}
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ext_ids |
{'doi': None, 'wikidata_qid': None, 'isbn13': None, 'pmid': None, 'pmcid': None, 'core': None, 'arxiv': '2102.05346v2', 'jstor': None, 'ark': None, 'mag': None, 'doaj': None, 'dblp': None, 'oai': None, 'hdl': None}
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files[] |
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