{"id":"https://openalex.org/W3194376875","doi":"https://doi.org/10.1109/icip42928.2021.9506031","title":"Localization Uncertainty-Based Attention For Object Detection","display_name":"Localization Uncertainty-Based Attention For Object Detection","publication_year":2021,"publication_date":"2021-08-23","ids":{"openalex":"https://openalex.org/W3194376875","doi":"https://doi.org/10.1109/icip42928.2021.9506031","mag":"3194376875"},"language":"en","primary_location":{"id":"doi:10.1109/icip42928.2021.9506031","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip42928.2021.9506031","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2108.11042","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034300560","display_name":"Sanghun Park","orcid":"https://orcid.org/0000-0001-5383-7005"},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sanghun Park","raw_affiliation_strings":["Pohang University of Science and Technology,Dept. of Computer Science and Engineering,Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pohang University of Science and Technology,Dept. of Computer Science and Engineering,Korea","institution_ids":["https://openalex.org/I123900574"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002845252","display_name":"Kunhee Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kunhee Kim","raw_affiliation_strings":["Pohang University of Science and Technology,Dept. of Computer Science and Engineering,Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pohang University of Science and Technology,Dept. of Computer Science and Engineering,Korea","institution_ids":["https://openalex.org/I123900574"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059041408","display_name":"Eunseop Lee","orcid":"https://orcid.org/0000-0002-6027-2863"},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Eunseop Lee","raw_affiliation_strings":["Pohang University of Science and Technology,Dept. of Computer Science and Engineering,Korea","Pohang University of Science and Technology, Pohang, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pohang University of Science and Technology,Dept. of Computer Science and Engineering,Korea","institution_ids":["https://openalex.org/I123900574"]},{"raw_affiliation_string":"Pohang University of Science and Technology, Pohang, South Korea","institution_ids":["https://openalex.org/I123900574"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101431617","display_name":"Daijin Kim","orcid":"https://orcid.org/0000-0002-8046-8521"},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]},{"id":"https://openalex.org/I4210151819","display_name":"St. Paul's Hospital","ror":"https://ror.org/04y7ajp38","country_code":"KR","type":"healthcare","lineage":["https://openalex.org/I4210151819"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Daijin Kim","raw_affiliation_strings":["Pohang University of Science and Technology,Dept. of Computer Science and Engineering,Korea","Catholic University of Korea, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pohang University of Science and Technology,Dept. of Computer Science and Engineering,Korea","institution_ids":["https://openalex.org/I123900574"]},{"raw_affiliation_string":"Catholic University of Korea, Seoul, South Korea","institution_ids":["https://openalex.org/I4210151819"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09849841,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2224","last_page":"2228"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9987999796867371,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9987000226974487,"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/benchmark","display_name":"Benchmark (surveying)","score":0.8017371892929077},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.7057703733444214},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.6968473196029663},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6906450986862183},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6791732311248779},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.6153311729431152},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5622706413269043},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5423583984375},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48712894320487976},{"id":"https://openalex.org/keywords/uncertainty-quantification","display_name":"Uncertainty quantification","score":0.4440634846687317},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.43662720918655396},{"id":"https://openalex.org/keywords/confidence-interval","display_name":"Confidence interval","score":0.42442458868026733},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.41636621952056885},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4068247079849243},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39252057671546936},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38056355714797974},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37267643213272095},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20039182901382446},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19158291816711426},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1302846372127533}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.8017371892929077},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.7057703733444214},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.6968473196029663},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6906450986862183},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6791732311248779},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.6153311729431152},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5622706413269043},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5423583984375},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48712894320487976},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.4440634846687317},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.43662720918655396},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.42442458868026733},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41636621952056885},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4068247079849243},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39252057671546936},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38056355714797974},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37267643213272095},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20039182901382446},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19158291816711426},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1302846372127533},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1109/icip42928.2021.9506031","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip42928.2021.9506031","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2108.11042","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2108.11042","pdf_url":"https://arxiv.org/pdf/2108.11042","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:3194376875","is_oa":true,"landing_page_url":"http://arxiv.org/pdf/2108.11042.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"pmh:oai:oasis.postech.ac.kr:2014.oak/109808","is_oa":false,"landing_page_url":"https://oasis.postech.ac.kr/handle/2014.oak/109808","pdf_url":null,"source":{"id":"https://openalex.org/S4306401965","display_name":"Open Access System for Information Sharing (Pohang University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I123900574","host_organization_name":"Pohang University of Science and Technology","host_organization_lineage":["https://openalex.org/I123900574"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference"},{"id":"doi:10.48550/arxiv.2108.11042","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2108.11042","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"},{"id":"doi:10.17023/fq6s-fj83","is_oa":true,"landing_page_url":"https://doi.org/10.17023/fq6s-fj83","pdf_url":null,"source":{"id":"https://openalex.org/S7407051697","display_name":"IEEE RESOURCE CENTERS","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2108.11042","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2108.11042","pdf_url":"https://arxiv.org/pdf/2108.11042","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.75}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3194376875.pdf","grobid_xml":"https://content.openalex.org/works/W3194376875.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1861492603","https://openalex.org/W2565639579","https://openalex.org/W2579985080","https://openalex.org/W2950141105","https://openalex.org/W2962677013","https://openalex.org/W2962766617","https://openalex.org/W2963150697","https://openalex.org/W2963299996","https://openalex.org/W2963351448","https://openalex.org/W2963786238","https://openalex.org/W2964241181","https://openalex.org/W2966926453","https://openalex.org/W2970575838","https://openalex.org/W2981958729","https://openalex.org/W2982770724","https://openalex.org/W2986357608","https://openalex.org/W2989604896","https://openalex.org/W3012573144","https://openalex.org/W3035396860","https://openalex.org/W6639102338","https://openalex.org/W6732243160","https://openalex.org/W6753494528","https://openalex.org/W6760947256","https://openalex.org/W6764322716","https://openalex.org/W6767109091"],"related_works":["https://openalex.org/W3177724741","https://openalex.org/W3189343424","https://openalex.org/W3112883392","https://openalex.org/W3161659397","https://openalex.org/W3126959070","https://openalex.org/W3175772341","https://openalex.org/W3048913829","https://openalex.org/W2560337053","https://openalex.org/W3206173524","https://openalex.org/W2952798805","https://openalex.org/W2526918431","https://openalex.org/W3170741396","https://openalex.org/W3014066851","https://openalex.org/W3201484206","https://openalex.org/W2127676094","https://openalex.org/W3133965884","https://openalex.org/W94418491","https://openalex.org/W1558119254","https://openalex.org/W3203461458","https://openalex.org/W2959623824"],"abstract_inverted_index":{"Object":[0],"detection":[1,14],"has":[2],"been":[3,50],"applied":[4],"in":[5,19],"a":[6,74,90,130],"wide":[7],"variety":[8],"of":[9,42,135],"real":[10],"world":[11],"scenarios,":[12],"so":[13],"algorithms":[15],"must":[16],"provide":[17],"confidence":[18,41,58,99],"the":[20,39,111,142],"results":[21],"to":[22,52,103],"ensure":[23],"that":[24,81,96,116,124],"appropriate":[25],"decisions":[26],"can":[27],"be":[28],"made":[29],"based":[30],"on":[31,137],"their":[32],"results.":[33],"Accordingly,":[34],"several":[35],"studies":[36],"have":[37,49],"investigated":[38],"probabilistic":[40],"bounding":[43],"box":[44,57,98],"regression.":[45],"However,":[46],"such":[47],"approaches":[48],"restricted":[51],"anchor-based":[53],"detectors,":[54],"which":[55],"use":[56],"values":[59],"as":[60],"additional":[61],"screening":[62],"scores":[63],"during":[64],"non-maximum":[65],"suppression":[66],"(NMS)":[67],"procedures.":[68],"In":[69],"this":[70],"paper,":[71],"we":[72],"propose":[73],"more":[75],"efficient":[76],"uncertainty-aware":[77],"dense":[78],"detector":[79],"(UADET)":[80],"predicts":[82],"four-directional":[83],"localization":[84],"uncertainties":[85],"via":[86],"Gaussian":[87],"modeling.":[88],"Furthermore,":[89],"simple":[91],"uncertainty":[92],"attention":[93],"module":[94],"(UAM)":[95],"exploits":[97],"maps":[100],"is":[101],"proposed":[102],"improve":[104],"performance":[105],"through":[106],"feature":[107],"refinement.":[108],"Experiments":[109],"using":[110],"MS":[112],"COCO":[113,138],"benchmark":[114],"show":[115],"our":[117,125],"UADET":[118],"consistently":[119],"surpasses":[120],"baseline":[121],"FCOS,":[122],"and":[123],"best":[126],"model,":[127,132],"ResNext-64x4d-101-DCN,":[128],"obtains":[129],"single":[131],"single-scale":[133],"AP":[134],"48.3%":[136],"test-dev,":[139],"thus":[140],"achieving":[141],"state-of-the-art":[143],"among":[144],"various":[145],"object":[146],"detectors.":[147]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}