{"id":"https://openalex.org/W3009136751","doi":"https://doi.org/10.1109/wacv45572.2020.9093553","title":"Analysis and a Solution of Momentarily Missed Detection for Anchor-based Object Detectors","display_name":"Analysis and a Solution of Momentarily Missed Detection for Anchor-based Object Detectors","publication_year":2020,"publication_date":"2020-03-01","ids":{"openalex":"https://openalex.org/W3009136751","doi":"https://doi.org/10.1109/wacv45572.2020.9093553","mag":"3009136751"},"language":"en","primary_location":{"id":"doi:10.1109/wacv45572.2020.9093553","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093553","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-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/A5082850746","display_name":"Yusuke Hosoya","orcid":null},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Yusuke Hosoya","raw_affiliation_strings":["Graduate School of Information Sciences, Tohoku University"],"affiliations":[{"raw_affiliation_string":"Graduate School of Information Sciences, Tohoku University","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042810984","display_name":"Masanori Suganuma","orcid":"https://orcid.org/0000-0002-1469-9663"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masanori Suganuma","raw_affiliation_strings":["Graduate School of Information Sciences, Tohoku University"],"affiliations":[{"raw_affiliation_string":"Graduate School of Information Sciences, Tohoku University","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009259465","display_name":"Takayuki Okatani","orcid":"https://orcid.org/0000-0001-9222-763X"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takayuki Okatani","raw_affiliation_strings":["Graduate School of Information Sciences, Tohoku University"],"affiliations":[{"raw_affiliation_string":"Graduate School of Information Sciences, Tohoku University","institution_ids":["https://openalex.org/I201537933"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5082850746"],"corresponding_institution_ids":["https://openalex.org/I201537933"],"apc_list":null,"apc_paid":null,"fwci":0.2931,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.54194394,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1399","last_page":"1407"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9997000098228455,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9997000098228455,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9991999864578247,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9991999864578247,"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/detector","display_name":"Detector","score":0.8400179147720337},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.7775102853775024},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7739028930664062},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.772520899772644},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7151644825935364},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6130790710449219},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5881716012954712},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5752173066139221},{"id":"https://openalex.org/keywords/motion-blur","display_name":"Motion blur","score":0.47176435589790344},{"id":"https://openalex.org/keywords/motion-detection","display_name":"Motion detection","score":0.45432746410369873},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.449836790561676},{"id":"https://openalex.org/keywords/object-class-detection","display_name":"Object-class detection","score":0.4214232265949249},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4130290150642395},{"id":"https://openalex.org/keywords/frame-rate","display_name":"Frame rate","score":0.4117473363876343},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.4057480990886688},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36075887084007263},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2137768268585205},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.18224963545799255},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10815545916557312},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.06923630833625793}],"concepts":[{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.8400179147720337},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7775102853775024},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7739028930664062},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.772520899772644},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7151644825935364},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6130790710449219},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5881716012954712},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5752173066139221},{"id":"https://openalex.org/C2777708103","wikidata":"https://www.wikidata.org/wiki/Q852589","display_name":"Motion blur","level":3,"score":0.47176435589790344},{"id":"https://openalex.org/C2780624872","wikidata":"https://www.wikidata.org/wiki/Q852453","display_name":"Motion detection","level":3,"score":0.45432746410369873},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.449836790561676},{"id":"https://openalex.org/C71681937","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object-class detection","level":5,"score":0.4214232265949249},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4130290150642395},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.4117473363876343},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.4057480990886688},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36075887084007263},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2137768268585205},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.18224963545799255},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10815545916557312},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.06923630833625793},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wacv45572.2020.9093553","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093553","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1686810756","https://openalex.org/W1861492603","https://openalex.org/W2031489346","https://openalex.org/W2129987527","https://openalex.org/W2158592639","https://openalex.org/W2194775991","https://openalex.org/W2291627510","https://openalex.org/W2528183205","https://openalex.org/W2549854571","https://openalex.org/W2560601110","https://openalex.org/W2565639579","https://openalex.org/W2570343428","https://openalex.org/W2579985080","https://openalex.org/W2605229288","https://openalex.org/W2613718673","https://openalex.org/W2761592212","https://openalex.org/W2793130599","https://openalex.org/W2810862788","https://openalex.org/W2899607431","https://openalex.org/W2916743882","https://openalex.org/W2949858991","https://openalex.org/W2955904076","https://openalex.org/W2962835968","https://openalex.org/W2963299996","https://openalex.org/W2963351448","https://openalex.org/W2963786238","https://openalex.org/W2964286567","https://openalex.org/W2982770724","https://openalex.org/W2989604896","https://openalex.org/W3012573144","https://openalex.org/W3106250896","https://openalex.org/W6620707391","https://openalex.org/W6637373629","https://openalex.org/W6639102338","https://openalex.org/W6679461745","https://openalex.org/W6696672603","https://openalex.org/W6729594559","https://openalex.org/W6732243160","https://openalex.org/W6752745451","https://openalex.org/W6753494528","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W2901758161","https://openalex.org/W4205668735","https://openalex.org/W3204852000","https://openalex.org/W3126664501","https://openalex.org/W3209429418","https://openalex.org/W4297540035","https://openalex.org/W2094004415","https://openalex.org/W4312834249","https://openalex.org/W3162303681","https://openalex.org/W3204216905"],"abstract_inverted_index":{"The":[0],"employment":[1],"of":[2,15,34,62,72,98,108,113,127],"convolutional":[3],"neural":[4],"networks":[5],"has":[6],"led":[7],"to":[8,23],"significant":[9],"performance":[10],"improvement":[11],"on":[12,77],"the":[13,60,68,82,96,109,114,125,137],"task":[14],"object":[16],"detection.":[17],"However,":[18],"when":[19,135],"applying":[20],"existing":[21],"detectors":[22,73,110],"continuous":[24],"frames":[25],"in":[26],"a":[27,43],"video,":[28],"we":[29,58,80],"often":[30],"encounter":[31],"momentary":[32],"miss-detection":[33,65,100],"objects,":[35],"that":[36,74],"is,":[37],"objects":[38],"are":[39,48,75],"undetected":[40],"exceptionally":[41],"at":[42,51,111],"few":[44],"frames,":[45],"although":[46],"they":[47],"correctly":[49],"detected":[50],"all":[52],"other":[53],"frames.":[54],"In":[55],"this":[56,119],"paper,":[57],"analyze":[59],"mechanism":[61],"how":[63],"such":[64,88],"occurs.":[66],"For":[67],"most":[69],"popular":[70],"class":[71],"based":[76],"anchor":[78,115,133],"boxes,":[79],"show":[81],"followings:":[83],"i)":[84],"besides":[85],"apparent":[86],"causes":[87],"as":[89],"motion":[90],"blur,":[91],"occlusions,":[92],"background":[93],"clutters,":[94],"etc.,":[95],"majority":[97],"remaining":[99],"can":[101,120],"be":[102,121],"explained":[103],"by":[104,123],"an":[105],"improper":[106],"behavior":[107],"boundaries":[112],"boxes;":[116],"and":[117],"ii)":[118],"rectified":[122],"improving":[124],"way":[126],"choosing":[128],"positive":[129],"samples":[130],"from":[131],"candidate":[132],"boxes":[134],"training":[136],"detectors.":[138]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}