{"id":"https://openalex.org/W2953554625","doi":"https://doi.org/10.1109/ivs.2019.8813771","title":"CNN-based synthesis of realistic high-resolution LiDAR data","display_name":"CNN-based synthesis of realistic high-resolution LiDAR data","publication_year":2019,"publication_date":"2019-06-01","ids":{"openalex":"https://openalex.org/W2953554625","doi":"https://doi.org/10.1109/ivs.2019.8813771","mag":"2953554625"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2019.8813771","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2019.8813771","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1907.00787","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Larissa T. Triess","orcid":null},"institutions":[{"id":"https://openalex.org/I891521709","display_name":"Daimler (Germany)","ror":"https://ror.org/00m0j3d84","country_code":"DE","type":"company","lineage":["https://openalex.org/I891521709"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Larissa T. Triess","raw_affiliation_strings":["Research and Development, Daimler AG, Stuttgart, Germany"],"affiliations":[{"raw_affiliation_string":"Research and Development, Daimler AG, Stuttgart, Germany","institution_ids":["https://openalex.org/I891521709"]}]},{"author_position":"middle","author":{"id":null,"display_name":"David Peter","orcid":null},"institutions":[{"id":"https://openalex.org/I891521709","display_name":"Daimler (Germany)","ror":"https://ror.org/00m0j3d84","country_code":"DE","type":"company","lineage":["https://openalex.org/I891521709"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"David Peter","raw_affiliation_strings":["Research and Development, Daimler AG, Stuttgart, Germany"],"affiliations":[{"raw_affiliation_string":"Research and Development, Daimler AG, Stuttgart, Germany","institution_ids":["https://openalex.org/I891521709"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Christoph B. Rist","orcid":null},"institutions":[{"id":"https://openalex.org/I891521709","display_name":"Daimler (Germany)","ror":"https://ror.org/00m0j3d84","country_code":"DE","type":"company","lineage":["https://openalex.org/I891521709"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Christoph B. Rist","raw_affiliation_strings":["Research and Development, Daimler AG, Stuttgart, Germany"],"affiliations":[{"raw_affiliation_string":"Research and Development, Daimler AG, Stuttgart, Germany","institution_ids":["https://openalex.org/I891521709"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Markus Enzweiler","orcid":null},"institutions":[{"id":"https://openalex.org/I891521709","display_name":"Daimler (Germany)","ror":"https://ror.org/00m0j3d84","country_code":"DE","type":"company","lineage":["https://openalex.org/I891521709"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Markus Enzweiler","raw_affiliation_strings":["Research and Development, Daimler AG, Stuttgart, Germany"],"affiliations":[{"raw_affiliation_string":"Research and Development, Daimler AG, Stuttgart, Germany","institution_ids":["https://openalex.org/I891521709"]}]},{"author_position":"last","author":{"id":null,"display_name":"J. Marius Zollner","orcid":null},"institutions":[{"id":"https://openalex.org/I143379178","display_name":"FZI Research Center for Information Technology","ror":"https://ror.org/04kdh6x72","country_code":"DE","type":"nonprofit","lineage":["https://openalex.org/I143379178"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"J. Marius Zollner","raw_affiliation_strings":["FZI Research Center for Information Technology, Karlsruhe, Germany"],"affiliations":[{"raw_affiliation_string":"FZI Research Center for Information Technology, Karlsruhe, Germany","institution_ids":["https://openalex.org/I143379178"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I891521709"],"apc_list":null,"apc_paid":null,"fwci":0.571,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.65231723,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1512","last_page":"1519"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.8181999921798706},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.8083000183105469},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.7261000275611877},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5950999855995178},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.48260000348091125},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.4731999933719635},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.46059998869895935}],"concepts":[{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.8181999921798706},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.8083000183105469},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7261000275611877},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6658999919891357},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5950999855995178},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5376999974250793},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.498199999332428},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.48260000348091125},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.47450000047683716},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.4731999933719635},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.46059998869895935},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.3544999957084656},{"id":"https://openalex.org/C141297171","wikidata":"https://www.wikidata.org/wiki/Q1143237","display_name":"Octree","level":2,"score":0.3499999940395355},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.31630000472068787},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.30649998784065247},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2980000078678131},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.2888000011444092}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ivs.2019.8813771","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2019.8813771","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1907.00787","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1907.00787","pdf_url":"https://arxiv.org/pdf/1907.00787","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1907.00787","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1907.00787","pdf_url":"https://arxiv.org/pdf/1907.00787","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W7682646","https://openalex.org/W1885185971","https://openalex.org/W2026726159","https://openalex.org/W2115579991","https://openalex.org/W2118273112","https://openalex.org/W2194775991","https://openalex.org/W2340897893","https://openalex.org/W2520322935","https://openalex.org/W2963186101","https://openalex.org/W2963316641","https://openalex.org/W2963470893","https://openalex.org/W2963680153","https://openalex.org/W6631190155","https://openalex.org/W6702130928","https://openalex.org/W6724647969","https://openalex.org/W6738279954","https://openalex.org/W6903590152"],"related_works":[],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,30,55,82,101],"novel":[4],"CNN-based":[5,115],"approach":[6,15],"for":[7],"synthesizing":[8],"high-resolution":[9],"LiDAR":[10,37],"point":[11,38,96],"cloud":[12],"data.":[13],"Our":[14,98],"generates":[16],"semantically":[17],"and":[18,70,104,110],"perceptually":[19],"realistic":[20],"results":[21,99],"with":[22,49],"guidance":[23],"from":[24],"specialized":[25],"loss-functions.":[26],"First,":[27],"we":[28,41,64,87],"utilize":[29],"modified":[31],"per-point":[32],"loss":[33],"that":[34],"addresses":[35],"missing":[36],"measurements.":[39],"Second,":[40],"align":[42],"the":[43,67,90],"quality":[44,92],"of":[45,93],"our":[46,75,94],"generated":[47,76,95],"output":[48],"real-world":[50,62],"sensor":[51],"data":[52,77],"by":[53],"applying":[54],"perceptual":[56,91],"loss.":[57],"In":[58,81],"large-scale":[59],"experiments":[60],"on":[61],"datasets,":[63],"evaluate":[65],"both":[66,108],"geometric":[68],"accuracy":[69],"semantic":[71],"segmentation":[72],"performance":[73],"using":[74],"vs.":[78],"ground":[79],"truth.":[80],"mean":[83],"opinion":[84],"score":[85],"testing":[86],"further":[88],"assess":[89],"clouds.":[97],"demonstrate":[100],"significant":[102],"quantitative":[103],"qualitative":[105],"improvement":[106],"in":[107],"geometry":[109],"semantics":[111],"over":[112],"traditional":[113],"non":[114],"upsampling":[116],"methods.":[117]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2019-07-12T00:00:00"}