{"id":"https://openalex.org/W3210161040","doi":"https://doi.org/10.1109/iv48863.2021.9575779","title":"Learning Semantics on Radar Point-Clouds","display_name":"Learning Semantics on Radar Point-Clouds","publication_year":2021,"publication_date":"2021-07-11","ids":{"openalex":"https://openalex.org/W3210161040","doi":"https://doi.org/10.1109/iv48863.2021.9575779","mag":"3210161040"},"language":"en","primary_location":{"id":"doi:10.1109/iv48863.2021.9575779","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv48863.2021.9575779","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036932595","display_name":"Simon T. Isele","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":"Simon T. Isele","raw_affiliation_strings":["Dr. Ing. h.c. F. Porsche AG, Weissach, Germany","FZI Research Center for Information Technology, Karlsruhe, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dr. Ing. h.c. F. Porsche AG, Weissach, Germany","institution_ids":[]},{"raw_affiliation_string":"FZI Research Center for Information Technology, Karlsruhe, Germany","institution_ids":["https://openalex.org/I143379178"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055757075","display_name":"Fabian E. Klein","orcid":null},"institutions":[{"id":"https://openalex.org/I134656947","display_name":"Esslingen University of Applied Sciences","ror":"https://ror.org/056cezx90","country_code":"DE","type":"education","lineage":["https://openalex.org/I134656947"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Fabian Klein","raw_affiliation_strings":["University of Esslingen, Esslingen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Esslingen, Esslingen, Germany","institution_ids":["https://openalex.org/I134656947"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075406031","display_name":"Mathis Brosowsky","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":"Mathis Brosowsky","raw_affiliation_strings":["Dr. Ing. h.c. F. Porsche AG, Weissach, Germany","FZI Research Center for Information Technology, Karlsruhe, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dr. Ing. h.c. F. Porsche AG, Weissach, Germany","institution_ids":[]},{"raw_affiliation_string":"FZI Research Center for Information Technology, Karlsruhe, Germany","institution_ids":["https://openalex.org/I143379178"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060028048","display_name":"J. Marius Z\u00f6llner","orcid":"https://orcid.org/0000-0001-6190-7202"},"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"],"raw_orcid":null,"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":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4578,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.59958894,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"810","last_page":"817"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9994000196456909,"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":0.9994000196456909,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9950000047683716,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7665290832519531},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6817482709884644},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.651534378528595},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.5709928274154663},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.5497421026229858},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5386121273040771},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.49968433380126953},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4929625988006592},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.46100494265556335},{"id":"https://openalex.org/keywords/concatenation","display_name":"Concatenation (mathematics)","score":0.42736053466796875},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.37136995792388916},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.103461354970932}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7665290832519531},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6817482709884644},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.651534378528595},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.5709928274154663},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.5497421026229858},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5386121273040771},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49968433380126953},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4929625988006592},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.46100494265556335},{"id":"https://openalex.org/C87619178","wikidata":"https://www.wikidata.org/wiki/Q126002","display_name":"Concatenation (mathematics)","level":2,"score":0.42736053466796875},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.37136995792388916},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.103461354970932},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iv48863.2021.9575779","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv48863.2021.9575779","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W2037227137","https://openalex.org/W2115579991","https://openalex.org/W2340897893","https://openalex.org/W2555254696","https://openalex.org/W2558294288","https://openalex.org/W2592152820","https://openalex.org/W2609719703","https://openalex.org/W2737996100","https://openalex.org/W2774756930","https://openalex.org/W2810641456","https://openalex.org/W2891649842","https://openalex.org/W2901136733","https://openalex.org/W2953303875","https://openalex.org/W2962731536","https://openalex.org/W2962912109","https://openalex.org/W2962928871","https://openalex.org/W2963121255","https://openalex.org/W2963727135","https://openalex.org/W2963954891","https://openalex.org/W2964128312","https://openalex.org/W2965376383","https://openalex.org/W2990710319","https://openalex.org/W2991216808","https://openalex.org/W2995042771","https://openalex.org/W2998614245","https://openalex.org/W3001808525","https://openalex.org/W3003437478","https://openalex.org/W3008115128","https://openalex.org/W3035172746","https://openalex.org/W3035275207","https://openalex.org/W3035574168","https://openalex.org/W3037211062","https://openalex.org/W3047223011","https://openalex.org/W3048683823","https://openalex.org/W3107627362","https://openalex.org/W3120926185","https://openalex.org/W3128392333","https://openalex.org/W3129347733","https://openalex.org/W3207554615","https://openalex.org/W6739778489","https://openalex.org/W6753266022","https://openalex.org/W6771922894","https://openalex.org/W6779595920","https://openalex.org/W6781274669","https://openalex.org/W6781920745","https://openalex.org/W6785770637","https://openalex.org/W6786733436"],"related_works":["https://openalex.org/W2373577936","https://openalex.org/W4319317934","https://openalex.org/W2901265155","https://openalex.org/W2956374172","https://openalex.org/W3095575180","https://openalex.org/W4319837668","https://openalex.org/W4293094720","https://openalex.org/W2739701376","https://openalex.org/W2562256921","https://openalex.org/W4392638253"],"abstract_inverted_index":{"Localization":[0],"and":[1,12,39,108,126],"perception":[2],"research":[3,79],"for":[4,147,178],"Autonomous":[5],"Driving":[6],"is":[7,61,136],"mainly":[8],"focused":[9],"on":[10,16,44,83,159],"camera":[11],"LiDAR":[13,71],"data,":[14],"rarely":[15],"radar":[17,30,84,103,123,145,160],"data.":[18,46,162],"We":[19],"apply":[20,40],"an":[21,49,58],"automated":[22],"labeling":[23],"pipeline":[24],"to":[25,36,54,64,88,110,155],"semantically":[26,141],"annotate":[27],"real":[28,143],"world":[29,144],"measurements,":[31],"manually":[32],"correct":[33],"point-wise":[34],"labels":[35],"obtain":[37],"ground-truth,":[38],"supervised":[41,152],"learning":[42,153],"models":[43],"this":[45],"To":[47],"assign":[48],"attribute,":[50],"called":[51],"class":[52],"label,":[53],"every":[55],"point":[56,85],"of":[57,70,102,172,175,185],"input":[59,95],"cloud":[60],"hereby":[62],"referred":[63],"as":[65],"semantic":[66,81,157],"segmentation.":[67],"Transferring":[68],"approaches":[69],"segmentation":[72,82,158],"into":[73],"the":[74,98,112],"similar":[75],"data":[76],"structure,":[77],"we":[78,117],"deep-learning":[80],"clouds.":[86],"Compared":[87],"classical":[89],"Cartesian":[90],"coordinates,":[91],"a":[92,140,173,182],"polar":[93],"coordinate":[94],"discretization":[96],"benefits":[97],"dynamically":[99],"changing":[100],"number":[101],"detections":[104],"per":[105],"sensing":[106],"cycle":[107],"simplifies":[109],"model":[111],"quasi-radial":[113],"sensor":[114],"resolution.":[115],"Moreover,":[116],"evaluate":[118],"different":[119],"network":[120,166],"architectures,":[121],"examine":[122],"feature":[124],"channels":[125],"also":[127],"temporal":[128],"consistency":[129],"by":[130],"attention":[131],"map":[132],"concatenation.":[133],"Our":[134,163],"contribution":[135],"twofold.":[137],"First,":[138],"featuring":[139],"labeled":[142],"dataset":[146],"ground":[148],"truth.":[149],"Second,":[150],"our":[151],"approach":[154],"solve":[156],"point-cloud":[161],"classification":[164],"benchmark":[165],"yields":[167],"56.1":[168],"%":[169],"weighted":[170],"Intersection":[171],"Union":[174],"relevant":[176],"classes":[177],"radar,":[179],"while":[180],"reaching":[181],"real-time":[183],"framerate":[184],"12.4ms.":[186]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
