{"id":"https://openalex.org/W3199897903","doi":"https://doi.org/10.1142/s1793351x21400067","title":"Decoupled Iterative Deep Sensor Fusion for 3D Semantic Segmentation","display_name":"Decoupled Iterative Deep Sensor Fusion for 3D Semantic Segmentation","publication_year":2021,"publication_date":"2021-09-01","ids":{"openalex":"https://openalex.org/W3199897903","doi":"https://doi.org/10.1142/s1793351x21400067","mag":"3199897903"},"language":"en","primary_location":{"id":"doi:10.1142/s1793351x21400067","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s1793351x21400067","pdf_url":null,"source":{"id":"https://openalex.org/S4210201727","display_name":"International Journal of Semantic Computing","issn_l":"1793-351X","issn":["1793-351X","1793-7108"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Semantic Computing","raw_type":"journal-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/A5050681793","display_name":"Fabian Duerr","orcid":"https://orcid.org/0009-0007-8552-635X"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Fabian Duerr","raw_affiliation_strings":["AUDI AG, 85057 Ingolstadt, Germany","Vision and Fusion Laboratory, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany"],"affiliations":[{"raw_affiliation_string":"AUDI AG, 85057 Ingolstadt, Germany","institution_ids":[]},{"raw_affiliation_string":"Vision and Fusion Laboratory, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany","institution_ids":["https://openalex.org/I102335020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001570322","display_name":"Hendrik Weigel","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hendrik Weigel","raw_affiliation_strings":["AUDI AG, 85057 Ingolstadt, Germany"],"affiliations":[{"raw_affiliation_string":"AUDI AG, 85057 Ingolstadt, Germany","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073930300","display_name":"J\u00fcrgen Beyerer","orcid":"https://orcid.org/0000-0003-3556-7181"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]},{"id":"https://openalex.org/I4210111500","display_name":"Fraunhofer Institute of Optronics, System Technologies and Image Exploitation","ror":"https://ror.org/01zx97922","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210111500","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"J\u00fcrgen Beyerer","raw_affiliation_strings":["Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (IOSB), Fraunhofer Center for Machine Learning, 76131 Karlsruhe, Germany","Vision and Fusion Laboratory, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany"],"affiliations":[{"raw_affiliation_string":"Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (IOSB), Fraunhofer Center for Machine Learning, 76131 Karlsruhe, Germany","institution_ids":["https://openalex.org/I4210111500"]},{"raw_affiliation_string":"Vision and Fusion Laboratory, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany","institution_ids":["https://openalex.org/I102335020"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5050681793"],"corresponding_institution_ids":["https://openalex.org/I102335020"],"apc_list":null,"apc_paid":null,"fwci":1.2779,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.87109026,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"15","issue":"03","first_page":"293","last_page":"312"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9995999932289124,"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"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9988999962806702,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9976999759674072,"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/point-cloud","display_name":"Point cloud","score":0.8514664173126221},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8408840894699097},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7356371879577637},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7275844812393188},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6757045984268188},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.6747915744781494},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6596617102622986},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5018279552459717},{"id":"https://openalex.org/keywords/iterative-closest-point","display_name":"Iterative closest point","score":0.45364025235176086},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.44310030341148376},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.4138528108596802},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.19883936643600464}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8514664173126221},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8408840894699097},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7356371879577637},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7275844812393188},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6757045984268188},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.6747915744781494},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6596617102622986},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5018279552459717},{"id":"https://openalex.org/C195958017","wikidata":"https://www.wikidata.org/wiki/Q1675268","display_name":"Iterative closest point","level":3,"score":0.45364025235176086},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.44310030341148376},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.4138528108596802},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.19883936643600464},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1142/s1793351x21400067","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s1793351x21400067","pdf_url":null,"source":{"id":"https://openalex.org/S4210201727","display_name":"International Journal of Semantic Computing","issn_l":"1793-351X","issn":["1793-351X","1793-7108"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Semantic Computing","raw_type":"journal-article"},{"id":"pmh:oai:fraunhofer.de:N-640551","is_oa":false,"landing_page_url":"http://publica.fraunhofer.de/documents/N-640551.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400801","display_name":"Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fraunhofer IOSB","raw_type":"Journal Article"},{"id":"pmh:oai:null:publica/269803","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/269803","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"journal article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.46000000834465027,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2117539524","https://openalex.org/W2150066425","https://openalex.org/W2340897893","https://openalex.org/W2412782625","https://openalex.org/W2604272474","https://openalex.org/W2612690371","https://openalex.org/W2788158258","https://openalex.org/W2795587607","https://openalex.org/W2798297823","https://openalex.org/W2894705404","https://openalex.org/W2896992394","https://openalex.org/W2951517617","https://openalex.org/W2955058313","https://openalex.org/W2963120444","https://openalex.org/W2963226018","https://openalex.org/W2963576229","https://openalex.org/W2964062501","https://openalex.org/W2964162504","https://openalex.org/W2990613095","https://openalex.org/W2991216808","https://openalex.org/W3003437478","https://openalex.org/W3035275207","https://openalex.org/W3035461736","https://openalex.org/W3035574168","https://openalex.org/W3039442820","https://openalex.org/W3093434340","https://openalex.org/W3109301572","https://openalex.org/W3117804044","https://openalex.org/W3122159272","https://openalex.org/W4212774754"],"related_works":["https://openalex.org/W4293094720","https://openalex.org/W2739701376","https://openalex.org/W2813834476","https://openalex.org/W3016861202","https://openalex.org/W2196111060","https://openalex.org/W2807666361","https://openalex.org/W4213431252","https://openalex.org/W2154495931","https://openalex.org/W2120071540","https://openalex.org/W4306760020"],"abstract_inverted_index":{"One":[0],"of":[1,14,31,53,88,99,166,191,199],"the":[2,47,100,125,141,145,164,167,189,192,197],"key":[3,71],"tasks":[4],"for":[5,63,73,85,202],"autonomous":[6,21],"vehicles":[7,22],"or":[8,23],"robots":[9,24],"is":[10,19,46,67],"a":[11,28,36,95],"robust":[12,37],"perception":[13],"their":[15,43],"3D":[16,44,54,74,89,203],"environment,":[17],"which":[18,92,118],"why":[20],"are":[25],"equipped":[26],"with":[27,150],"wide":[29],"range":[30,96,179],"different":[32,138],"sensors.":[33],"Building":[34],"upon":[35,94],"sensor":[38,55],"setup,":[39],"understanding":[40],"and":[41,66,103,111,121,131,134,159,182,196],"interpreting":[42],"environment":[45],"next":[48],"important":[49],"step.":[50],"Semantic":[51],"segmentation":[52,87],"data,":[56],"e.g.":[57],"point":[58,90,101],"clouds,":[59,91],"provides":[60],"valuable":[61],"information":[62],"this":[64],"task":[65],"often":[68],"seen":[69],"as":[70,153,155],"enabler":[72],"scene":[75],"understanding.":[76],"This":[77],"work":[78],"presents":[79],"an":[80],"iterative":[81,169],"deep":[82,170],"fusion":[83,127,171,183,194],"architecture":[84],"semantic":[86,204],"builds":[93],"image":[97],"representation":[98],"clouds":[102],"additionally":[104],"exploits":[105],"camera":[106,122,135,151,160,200],"features":[107,123,136,201],"to":[108,115],"increase":[109],"accuracy":[110],"robustness.":[112],"In":[113],"contrast":[114],"other":[116],"approaches,":[117],"fuse":[119],"lidar":[120,133,158,181],"once,":[124],"proposed":[126,146,193],"strategy":[128,195],"iteratively":[129],"combines":[130],"refines":[132],"at":[137],"scales":[139],"inside":[140],"network":[142],"architecture.":[143],"Additionally,":[144],"approach":[147,172],"can":[148],"deal":[149],"failure":[152],"well":[154],"jointly":[156],"predict":[157],"segmentation.":[161,205],"We":[162],"demonstrate":[163],"benefits":[165],"presented":[168],"on":[173],"two":[174],"challenging":[175],"datasets,":[176],"outperforming":[177],"all":[178],"image-based":[180],"approaches.":[184],"An":[185],"in-depth":[186],"evaluation":[187],"underlines":[188],"effectiveness":[190],"potential":[198]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
