{"id":"https://openalex.org/W4393158977","doi":"https://doi.org/10.1609/aaai.v38i2.27921","title":"Hyp-OW: Exploiting Hierarchical Structure Learning with Hyperbolic Distance Enhances Open World Object Detection","display_name":"Hyp-OW: Exploiting Hierarchical Structure Learning with Hyperbolic Distance Enhances Open World Object Detection","publication_year":2024,"publication_date":"2024-03-24","ids":{"openalex":"https://openalex.org/W4393158977","doi":"https://doi.org/10.1609/aaai.v38i2.27921"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v38i2.27921","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v38i2.27921","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/27921/27864","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/27921/27864","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5080464225","display_name":"Thang Doan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210151956","display_name":"Robert Bosch (India)","ror":"https://ror.org/04my8ty22","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210151956","https://openalex.org/I889804353"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Thang Doan","raw_affiliation_strings":["Bosch Research North America & Bosch Center for Artificial Intelligence"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bosch Research North America & Bosch Center for Artificial Intelligence","institution_ids":["https://openalex.org/I4210151956"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101876783","display_name":"Xin Li","orcid":"https://orcid.org/0000-0003-4672-1500"},"institutions":[{"id":"https://openalex.org/I4210151956","display_name":"Robert Bosch (India)","ror":"https://ror.org/04my8ty22","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210151956","https://openalex.org/I889804353"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Xin Li","raw_affiliation_strings":["Bosch Research North America & Bosch Center for Artificial Intelligence"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bosch Research North America & Bosch Center for Artificial Intelligence","institution_ids":["https://openalex.org/I4210151956"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023212176","display_name":"Sima Behpour","orcid":null},"institutions":[{"id":"https://openalex.org/I4210151956","display_name":"Robert Bosch (India)","ror":"https://ror.org/04my8ty22","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210151956","https://openalex.org/I889804353"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sima Behpour","raw_affiliation_strings":["Bosch Research North America & Bosch Center for Artificial Intelligence"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bosch Research North America & Bosch Center for Artificial Intelligence","institution_ids":["https://openalex.org/I4210151956"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100351700","display_name":"Wenbin He","orcid":"https://orcid.org/0000-0003-1700-6057"},"institutions":[{"id":"https://openalex.org/I4210151956","display_name":"Robert Bosch (India)","ror":"https://ror.org/04my8ty22","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210151956","https://openalex.org/I889804353"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Wenbin He","raw_affiliation_strings":["Bosch Research North America & Bosch Center for Artificial Intelligence"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bosch Research North America & Bosch Center for Artificial Intelligence","institution_ids":["https://openalex.org/I4210151956"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103084682","display_name":"Liang Gou","orcid":"https://orcid.org/0009-0006-9138-3351"},"institutions":[{"id":"https://openalex.org/I4210151956","display_name":"Robert Bosch (India)","ror":"https://ror.org/04my8ty22","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210151956","https://openalex.org/I889804353"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Liang Gou","raw_affiliation_strings":["Bosch Research North America & Bosch Center for Artificial Intelligence"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bosch Research North America & Bosch Center for Artificial Intelligence","institution_ids":["https://openalex.org/I4210151956"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103725392","display_name":"Liu Ren","orcid":null},"institutions":[{"id":"https://openalex.org/I4210151956","display_name":"Robert Bosch (India)","ror":"https://ror.org/04my8ty22","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210151956","https://openalex.org/I889804353"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Liu Ren","raw_affiliation_strings":["Bosch Research North America & Bosch Center for Artificial Intelligence"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bosch Research North America & Bosch Center for Artificial Intelligence","institution_ids":["https://openalex.org/I4210151956"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210151956"],"apc_list":null,"apc_paid":null,"fwci":4.9323,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.96251742,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"38","issue":"2","first_page":"1555","last_page":"1563"},"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":0.9922999739646912,"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":0.9922999739646912,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9793000221252441,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9771000146865845,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4847823977470398},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4503176212310791},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.413499116897583},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34852689504623413},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3478241562843323},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.34128832817077637}],"concepts":[{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4847823977470398},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4503176212310791},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.413499116897583},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34852689504623413},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3478241562843323},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.34128832817077637}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v38i2.27921","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v38i2.27921","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/27921/27864","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v38i2.27921","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v38i2.27921","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/27921/27864","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4393158977.pdf"},"referenced_works_count":65,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W2194775991","https://openalex.org/W2222512263","https://openalex.org/W2250539671","https://openalex.org/W2489487449","https://openalex.org/W2560647685","https://openalex.org/W2804622816","https://openalex.org/W2867167548","https://openalex.org/W2930957955","https://openalex.org/W2934497416","https://openalex.org/W2955067198","https://openalex.org/W3035700349","https://openalex.org/W3091908876","https://openalex.org/W3092462694","https://openalex.org/W3102616566","https://openalex.org/W3120411988","https://openalex.org/W3133661165","https://openalex.org/W3152259014","https://openalex.org/W3159481202","https://openalex.org/W3160582676","https://openalex.org/W3168619736","https://openalex.org/W3176709420","https://openalex.org/W3176793698","https://openalex.org/W3194038966","https://openalex.org/W3194737599","https://openalex.org/W3217535672","https://openalex.org/W4221156521","https://openalex.org/W4223978083","https://openalex.org/W4226398978","https://openalex.org/W4280603059","https://openalex.org/W4285580089","https://openalex.org/W4288055634","https://openalex.org/W4295111765","https://openalex.org/W4295112092","https://openalex.org/W4296899566","https://openalex.org/W4301366329","https://openalex.org/W4308236039","https://openalex.org/W4310500528","https://openalex.org/W4310820030","https://openalex.org/W4312533318","https://openalex.org/W4312894362","https://openalex.org/W4312925417","https://openalex.org/W4313018996","https://openalex.org/W4313153237","https://openalex.org/W4313189668","https://openalex.org/W4319235394","https://openalex.org/W4319323243","https://openalex.org/W4385210137","https://openalex.org/W4385946815","https://openalex.org/W4386076022","https://openalex.org/W4386076409","https://openalex.org/W4389650633","https://openalex.org/W6639102338","https://openalex.org/W6687483927","https://openalex.org/W6689029123","https://openalex.org/W6691431627","https://openalex.org/W6760614615","https://openalex.org/W6785458781","https://openalex.org/W6786097111","https://openalex.org/W6792296345","https://openalex.org/W6797967155","https://openalex.org/W6805158924","https://openalex.org/W6810994575","https://openalex.org/W6843214225","https://openalex.org/W6845191053"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2775347418","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Open":[0],"World":[1],"Object":[2,18],"Detection":[3,19],"(OWOD)":[4],"is":[5,51],"a":[6,49,59,68,91,113,125,139,177],"challenging":[7],"and":[8,26,100,117,159,184],"realistic":[9],"task":[10],"that":[11,73,115],"extends":[12],"beyond":[13],"the":[14,37,45,56,82,98,150],"scope":[15],"of":[16,39,55,121,152],"standard":[17],"task.":[20],"It":[21],"involves":[22],"detecting":[23],"both":[24,157],"known":[25,83,99,122,158,183],"unknown":[27,101,136,160,185],"objects":[28,137],"while":[29],"integrating":[30],"learned":[31],"knowledge":[32],"for":[33],"future":[34],"tasks.":[35],"However,":[36],"level":[38],"\"unknownness\"":[40],"varies":[41],"significantly":[42],"depending":[43],"on":[44,146],"context.":[46,70],"For":[47],"example,":[48],"tree":[50],"typically":[52],"considered":[53],"part":[54],"background":[57],"in":[58,67,156,171],"self-driving":[60],"scene,":[61],"but":[62],"it":[63],"may":[64],"be":[65,79,90,104],"significant":[66],"household":[69],"We":[71],"argue":[72],"this":[74,108,129],"contextual":[75],"information":[76],"should":[77,89],"already":[78],"embedded":[80],"within":[81],"classes.":[84],"In":[85],"other":[86],"words,":[87],"there":[88],"semantic":[92],"or":[93],"latent":[94],"structure":[95,180],"relationship":[96],"between":[97,182],"items":[102,123],"to":[103,133,163],"discovered.":[105],"Motivated":[106],"by":[107],"observation,":[109],"we":[110],"propose":[111],"Hyp-OW,":[112,153],"method":[114],"learns":[116],"models":[118],"hierarchical":[119,179],"representation":[120,130],"through":[124],"SuperClass":[126],"Regularizer.":[127],"Leveraging":[128],"allows":[131],"us":[132],"effectively":[134],"detect":[135],"using":[138],"similarity":[140],"distance-based":[141],"relabeling":[142],"module.":[143],"Extensive":[144],"experiments":[145],"benchmark":[147],"datasets":[148],"demonstrate":[149],"effectiveness":[151],"achieving":[154],"improvement":[155],"detection":[161],"(up":[162],"6":[164],"percent).":[165],"These":[166],"findings":[167],"are":[168],"particularly":[169],"pronounced":[170],"our":[172],"newly":[173],"designed":[174],"benchmark,":[175],"where":[176],"strong":[178],"exists":[181],"objects.":[186]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4}],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2025-10-10T00:00:00"}
