{"id":"https://openalex.org/W4401416672","doi":"https://doi.org/10.1109/icra57147.2024.10610801","title":"WLST: Weak Labels Guided Self-training for Weakly-supervised Domain Adaptation on 3D Object Detection","display_name":"WLST: Weak Labels Guided Self-training for Weakly-supervised Domain Adaptation on 3D Object Detection","publication_year":2024,"publication_date":"2024-05-13","ids":{"openalex":"https://openalex.org/W4401416672","doi":"https://doi.org/10.1109/icra57147.2024.10610801"},"language":"en","primary_location":{"id":"doi:10.1109/icra57147.2024.10610801","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icra57147.2024.10610801","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5040760735","display_name":"Tsung-Lin Tsou","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Tsung-Lin Tsou","raw_affiliation_strings":["National Taiwan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104085526","display_name":"Tsung-Han Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Tsung-Han Wu","raw_affiliation_strings":["National Taiwan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043898632","display_name":"Winston H. Hsu","orcid":"https://orcid.org/0000-0002-3330-0638"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Winston H. Hsu","raw_affiliation_strings":["National Taiwan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University","institution_ids":["https://openalex.org/I16733864"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I16733864"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"30","issue":null,"first_page":"18214","last_page":"18220"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9997000098228455,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9997000098228455,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9994999766349792,"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/domain-adaptation","display_name":"Domain adaptation","score":0.8509892225265503},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7095766067504883},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.680099368095398},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6523220539093018},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5549182891845703},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5466828346252441},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5255210399627686},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4885193109512329},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.4386933743953705},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4310864210128784},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38574835658073425},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.1734132468700409},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1637476682662964},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.06921067833900452}],"concepts":[{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.8509892225265503},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7095766067504883},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.680099368095398},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6523220539093018},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5549182891845703},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5466828346252441},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5255210399627686},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4885193109512329},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4386933743953705},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4310864210128784},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38574835658073425},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.1734132468700409},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1637476682662964},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.06921067833900452},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra57147.2024.10610801","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icra57147.2024.10610801","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320308258","display_name":"Qualcomm","ror":"https://ror.org/002zrf773"},{"id":"https://openalex.org/F4320331164","display_name":"National Science and Technology Council","ror":"https://ror.org/00wnb9798"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W2150066425","https://openalex.org/W2897529137","https://openalex.org/W2949708697","https://openalex.org/W2963121255","https://openalex.org/W2963727135","https://openalex.org/W2964062501","https://openalex.org/W2964241181","https://openalex.org/W2968296999","https://openalex.org/W2981581281","https://openalex.org/W2981949127","https://openalex.org/W3008105217","https://openalex.org/W3034314779","https://openalex.org/W3034975685","https://openalex.org/W3035172746","https://openalex.org/W3035574168","https://openalex.org/W3036853234","https://openalex.org/W3113028524","https://openalex.org/W3118341329","https://openalex.org/W3130463448","https://openalex.org/W3134233478","https://openalex.org/W3167095230","https://openalex.org/W3175269419","https://openalex.org/W3195311297","https://openalex.org/W3207105331","https://openalex.org/W4230769173","https://openalex.org/W4236965008","https://openalex.org/W4285102119","https://openalex.org/W4310078553","https://openalex.org/W4312382205","https://openalex.org/W4313007055","https://openalex.org/W6739778489","https://openalex.org/W6763422710","https://openalex.org/W6779564934"],"related_works":["https://openalex.org/W4394775207","https://openalex.org/W4389474468","https://openalex.org/W4300172004","https://openalex.org/W4321649381","https://openalex.org/W2997645659","https://openalex.org/W3180787869","https://openalex.org/W3203792196","https://openalex.org/W2955455867","https://openalex.org/W4295929828","https://openalex.org/W3156096827"],"abstract_inverted_index":{"In":[0],"the":[1,13,27,31,35,48,68,73,111,130,134,140,168],"field":[2],"of":[3,12,145],"domain":[4,19,52],"adaptation":[5,20,53],"(DA)":[6],"on":[7,67,93,133,155,175],"3D":[8,94,103],"object":[9,95],"detection,":[10],"most":[11],"work":[14],"is":[15,38,42,55,117,173],"dedicated":[16],"to":[17,119],"unsupervised":[18],"(UDA).":[21],"Yet,":[22],"without":[23],"any":[24],"target":[25,69,135],"annotations,":[26],"performance":[28,75],"gap":[29],"between":[30],"UDA":[32],"approaches":[33],"and":[34,123,143,160],"fully-supervised":[36],"approach":[37],"still":[39],"noticeable,":[40],"which":[41,100],"impractical":[43],"for":[44,91],"real-world":[45],"applications.":[46],"On":[47],"other":[49],"hand,":[50],"weakly-supervised":[51],"(WDA)":[54],"an":[56],"underexplored":[57],"yet":[58],"practical":[59],"task":[60],"that":[61,127,167],"only":[62],"requires":[63],"few":[64],"labeling":[65],"effort":[66],"domain.":[70,136],"To":[71],"improve":[72],"DA":[74],"in":[76],"a":[77,82],"cost-effective":[78],"way,":[79],"we":[80],"propose":[81],"general":[83],"weak":[84],"labels":[85,105,126],"guided":[86],"self-training":[87,113],"framework,":[88],"WLST,":[89],"designed":[90],"WDA":[92],"detection.":[96],"By":[97],"incorporating":[98],"autolabeler,":[99],"can":[101],"generate":[102,120],"pseudo":[104,125],"from":[106],"2D":[107],"bounding":[108],"boxes,":[109],"into":[110],"existing":[112],"pipeline,":[114],"our":[115,146],"method":[116],"able":[118],"more":[121],"robust":[122],"consistent":[124],"would":[128],"benefit":[129],"training":[131],"process":[132],"Extensive":[137],"experiments":[138],"demonstrate":[139],"effectiveness,":[141],"robustness,":[142],"detector-agnosticism":[144],"WLST":[147],"framework.":[148],"Notably,":[149],"it":[150],"outperforms":[151],"previous":[152],"state-of-the-art":[153],"methods":[154],"all":[156],"evaluation":[157],"tasks.":[158],"Code":[159],"models":[161],"are":[162],"available":[163,174],"at":[164],"https://github.com/jacky121298/WLST.":[165],"Note":[166],"complete":[169],"version":[170],"with":[171],"appendix":[172],"arXiv.":[176]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}