{"id":"https://openalex.org/W4387129532","doi":"https://doi.org/10.1109/lra.2023.3320488","title":"Discwise Active Learning for LiDAR Semantic Segmentation","display_name":"Discwise Active Learning for LiDAR Semantic Segmentation","publication_year":2023,"publication_date":"2023-09-28","ids":{"openalex":"https://openalex.org/W4387129532","doi":"https://doi.org/10.1109/lra.2023.3320488"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2023.3320488","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2023.3320488","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","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/A5090395353","display_name":"Ozan Unal","orcid":"https://orcid.org/0000-0002-1121-3883"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":true,"raw_author_name":"Ozan Unal","raw_affiliation_strings":["Computer Vision Lab, ETH Zurich, Zurich, Switzerland"],"affiliations":[{"raw_affiliation_string":"Computer Vision Lab, ETH Zurich, Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078838951","display_name":"Dengxin Dai","orcid":"https://orcid.org/0000-0001-5440-9678"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dengxin Dai","raw_affiliation_strings":["Huawei Technologies, Zurich Research Center, Zurich, Switzerland"],"affiliations":[{"raw_affiliation_string":"Huawei Technologies, Zurich Research Center, Zurich, Switzerland","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061396778","display_name":"Ali Tamer \u00dcnal","orcid":"https://orcid.org/0000-0002-6417-745X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ali Tamer Unal","raw_affiliation_strings":["Department of Industrial Engineering, Bo&#x011F;azi&#x00E7;i University, Istanbul, T&#x00FC;rkiye"],"affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, Bo&#x011F;azi&#x00E7;i University, Istanbul, T&#x00FC;rkiye","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001254143","display_name":"Luc Van Gool","orcid":"https://orcid.org/0000-0002-3445-5711"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]},{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE","CH"],"is_corresponding":false,"raw_author_name":"Luc Van Gool","raw_affiliation_strings":["Computer Vision Lab, ETH Zurich, Zurich, Switzerland","Computer Vision Lab, ETH Zurich, Zurich, Switzerland; INSAIT, Sofia, Belgium; VISICS, ESAT/PSI, KU Leuven, Leuven, Belgium"],"affiliations":[{"raw_affiliation_string":"Computer Vision Lab, ETH Zurich, Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]},{"raw_affiliation_string":"Computer Vision Lab, ETH Zurich, Zurich, Switzerland; INSAIT, Sofia, Belgium; VISICS, ESAT/PSI, KU Leuven, Leuven, Belgium","institution_ids":["https://openalex.org/I99464096","https://openalex.org/I35440088"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5090395353"],"corresponding_institution_ids":["https://openalex.org/I35440088"],"apc_list":null,"apc_paid":null,"fwci":0.5219,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.72112017,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":"8","issue":"11","first_page":"7671","last_page":"7678"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.9973999857902527,"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"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9970999956130981,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8267455101013184},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.7325625419616699},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.720310628414154},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.7056196331977844},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5969646573066711},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5742499828338623},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4830089807510376},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.39294931292533875},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34408843517303467},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.09225007891654968}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8267455101013184},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.7325625419616699},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.720310628414154},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7056196331977844},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5969646573066711},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5742499828338623},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4830089807510376},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39294931292533875},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34408843517303467},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.09225007891654968},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2023.3320488","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2023.3320488","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4300000071525574,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W582134693","https://openalex.org/W1580210754","https://openalex.org/W1983521647","https://openalex.org/W2010588484","https://openalex.org/W2124244761","https://openalex.org/W2171671120","https://openalex.org/W2471138382","https://openalex.org/W2560609797","https://openalex.org/W2951061410","https://openalex.org/W2951786554","https://openalex.org/W2953070460","https://openalex.org/W2962912109","https://openalex.org/W2963121255","https://openalex.org/W2963125977","https://openalex.org/W2964073328","https://openalex.org/W2968557240","https://openalex.org/W2991216808","https://openalex.org/W3035166710","https://openalex.org/W3108580372","https://openalex.org/W3109154950","https://openalex.org/W3118723358","https://openalex.org/W3129517581","https://openalex.org/W3153635465","https://openalex.org/W3177330511","https://openalex.org/W3198790326","https://openalex.org/W3202349074","https://openalex.org/W3203978358","https://openalex.org/W3206841217","https://openalex.org/W4312350487","https://openalex.org/W4312812384","https://openalex.org/W4312828305","https://openalex.org/W6617145748","https://openalex.org/W6733814495","https://openalex.org/W6735374517","https://openalex.org/W6739778489","https://openalex.org/W6763422710","https://openalex.org/W6764588566"],"related_works":["https://openalex.org/W4319317934","https://openalex.org/W2901265155","https://openalex.org/W2956374172","https://openalex.org/W4319837668","https://openalex.org/W4308071650","https://openalex.org/W3188333020","https://openalex.org/W1964041166","https://openalex.org/W4390887692","https://openalex.org/W4210818033","https://openalex.org/W4388446985"],"abstract_inverted_index":{"While":[0],"LiDAR":[1,49],"data":[2],"acquisition":[3,122],"is":[4,56],"easy,":[5],"labeling":[6,68,73,101],"for":[7,48],"semantic":[8,50],"segmentation":[9],"remains":[10],"highly":[11],"time":[12],"consuming":[13],"and":[14,29,38,182],"must":[15,65],"therefore":[16,80],"be":[17],"done":[18],"selectively.":[19],"Active":[20],"learning":[21,173],"(AL)":[22],"provides":[23,149],"a":[24,32,39,53,57,62,82,94,120,144,150,171],"solution":[25,152],"that":[26,74,112,124,148],"can":[27],"iteratively":[28],"intelligently":[30],"label":[31],"dataset":[33,181],"while":[34,159],"retaining":[35],"high":[36],"performance":[37],"low":[40],"budget.":[41],"In":[42],"this":[43],"work":[44],"we":[45,90,118,142,169],"explore":[46],"AL":[47],"segmentation.":[51],"As":[52],"human":[54],"expert":[55],"component":[58],"of":[59,156,165],"the":[60,92,108,154,163],"pipeline,":[61],"practical":[63],"framework":[64],"consider":[66],"common":[67],"techniques":[69],"such":[70],"as":[71],"sequential":[72],"drastically":[75],"improve":[76,183],"annotation":[77],"times.":[78],"We":[79,105],"propose":[81,170],"discwise":[83,115],"approach":[84,174],"(DiAL),":[85],"where":[86],"in":[87],"each":[88],"iteration,":[89],"query":[91],"region":[93],"single":[95],"frame":[96],"covers":[97],"on":[98],"global":[99],"coordinates,":[100],"all":[102,177],"frames":[103,158,178],"simultaneously.":[104],"then":[106],"tackle":[107],"two":[109],"major":[110],"challenges":[111],"emerge":[113],"with":[114],"AL.":[116],"Firstly,":[117],"devise":[119],"new":[121],"function":[123],"takes":[125],"3D":[126],"point":[127],"density":[128],"changes":[129,137],"into":[130,161],"consideration":[131,162],"which":[132],"arise":[133],"due":[134],"to":[135,153,175],"location":[136],"or":[138],"ego-vehicle":[139],"motion.":[140],"Next,":[141],"solve":[143],"mixed-integer":[145],"linear":[146],"program":[147],"general":[151],"selection":[155],"multiple":[157],"taking":[160],"possibilities":[164],"disc":[166],"intersections.":[167],"Finally":[168],"semi-supervised":[172],"utilize":[176],"within":[179],"our":[180],"performance.":[184]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
