{"id":"https://openalex.org/W3160467996","doi":"https://doi.org/10.1109/icpr48806.2021.9412038","title":"DualBox: Generating BBox Pair with Strong Correspondence via Occlusion Pattern Clustering and Proposal Refinement","display_name":"DualBox: Generating BBox Pair with Strong Correspondence via Occlusion Pattern Clustering and Proposal Refinement","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3160467996","doi":"https://doi.org/10.1109/icpr48806.2021.9412038","mag":"3160467996"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412038","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412038","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","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/A5103095930","display_name":"Zheng Ge","orcid":"https://orcid.org/0000-0001-8770-2555"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Zheng Ge","raw_affiliation_strings":["Graduate School of Information, Production and Systems, Waseda University, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Information, Production and Systems, Waseda University, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071546638","display_name":"Chuyu Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Chuyu Hu","raw_affiliation_strings":["Graduate School of Information, Production and Systems, Waseda University, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Information, Production and Systems, Waseda University, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047677335","display_name":"Xin Huang","orcid":"https://orcid.org/0000-0001-7113-5066"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Xin Huang","raw_affiliation_strings":["Graduate School of Information, Production and Systems, Waseda University, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Information, Production and Systems, Waseda University, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026154649","display_name":"Baiqiao Qiu","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Baiqiao Qiu","raw_affiliation_strings":["Graduate School of Information, Production and Systems, Waseda University, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Information, Production and Systems, Waseda University, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057487414","display_name":"Osamu Yoshie","orcid":"https://orcid.org/0000-0002-4192-554X"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Osamu Yoshie","raw_affiliation_strings":["Graduate School of Information, Production and Systems, Waseda University, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Information, Production and Systems, Waseda University, Japan","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5103095930"],"corresponding_institution_ids":["https://openalex.org/I150744194"],"apc_list":null,"apc_paid":null,"fwci":0.1921,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.46645425,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2097","last_page":"2102"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9991000294685364,"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":0.9991000294685364,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9976000189781189,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/cluster-analysis","display_name":"Cluster analysis","score":0.6396012902259827},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5768681168556213},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.5219118595123291},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5008430480957031},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35144758224487305}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6396012902259827},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5768681168556213},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.5219118595123291},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5008430480957031},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35144758224487305}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412038","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412038","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.5099999904632568}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2107775979","https://openalex.org/W2194775991","https://openalex.org/W2200528286","https://openalex.org/W2340897893","https://openalex.org/W2565639579","https://openalex.org/W2594507094","https://openalex.org/W2613718673","https://openalex.org/W2752782242","https://openalex.org/W2775890136","https://openalex.org/W2792824754","https://openalex.org/W2798542761","https://openalex.org/W2883363148","https://openalex.org/W2887564556","https://openalex.org/W2894820835","https://openalex.org/W2963150697","https://openalex.org/W2963420686","https://openalex.org/W2963681621","https://openalex.org/W2963769056","https://openalex.org/W2964241181","https://openalex.org/W2990075400","https://openalex.org/W3011654159","https://openalex.org/W3034638324","https://openalex.org/W4288103659","https://openalex.org/W6620707391","https://openalex.org/W6753388331"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Despite":[0],"the":[1,7,17,49,60,68,99,103,116,129,134,153,160,201,204,208],"rapid":[2],"development":[3],"of":[4,9,20,27,105,118,137,152,203],"pedestrian":[5,11],"detection,":[6],"problem":[8],"dense":[10],"detection":[12],"is":[13,36],"still":[14],"unsolved,":[15],"especially":[16,231],"upper":[18],"limit":[19],"Recall":[21],"caused":[22,132],"by":[23,47,133],"Non-Maximum-Suppression":[24],"(NMS).":[25],"Out":[26],"this":[28],"reason,":[29],"R":[30,75,106,182],"<sup":[31,76,107,183],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[32,77,108,184],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[33,78,109,185],"NMS":[34,61,79],"[1]":[35],"proposed":[37,73,205],"to":[38,127,158],"simultaneously":[39],"detect":[40],"full":[41,50,84,123,167],"and":[42,70,85,101,170,211,228],"visible":[43,56,86,119,139,163],"body":[44,51,57,87,120,124,140,168],"bounding":[45],"boxes,":[46],"replacing":[48],"BBoxes":[52,58],"with":[53,181],"less":[54],"occluded":[55,229,233],"in":[59,74],"algorithm,":[62],"achieving":[63],"a":[64,144],"higher":[65],"recall.":[66],"However,":[67],"P-RPN":[69],"P-RCNN":[71],"modules":[72],"for":[80,94,165,224],"simultaneous":[81],"high":[82],"quality":[83],"prediction":[88,148],"require":[89],"non-trivial":[90],"positive/negative":[91],"assigning":[92],"strategies":[93],"anchor":[95],"BBoxes.":[96],"To":[97],"simplify":[98],"prerequisites":[100],"improve":[102],"utility":[104],"NMS,":[110,186],"we":[111,142],"incorporate":[112],"clustering":[113],"analysis":[114],"into":[115,174],"learning":[117],"proposals":[121,164,169],"from":[122],"proposals.":[125],"Furthermore,":[126],"reduce":[128],"computation":[130],"complexity":[131],"large":[135],"number":[136],"potential":[138],"proposals,":[141],"introduce":[143],"novel":[145],"occlusion":[146],"pattern":[147],"branch":[149],"on":[150,207],"top":[151],"R-CNN":[154,176],"module":[155,177],"(i.e.":[156,178],"F-RCNN)":[157],"select":[159],"best":[161],"matched":[162],"each":[166],"then":[171],"feed":[172],"them":[173],"another":[175],"V-RCNN).":[179],"Incorporated":[180],"our":[187,219],"DualBox":[188],"model":[189],"can":[190],"achieve":[191],"competitive":[192],"performance":[193,223],"while":[194],"only":[195],"requires":[196],"few":[197],"hyper-parameters.":[198],"We":[199],"validate":[200],"effectiveness":[202],"approach":[206,220],"CrowdHuman":[209],"[2]":[210],"CityPersons":[212],"[3]":[213],"datasets.":[214],"Experimental":[215],"results":[216],"show":[217],"that":[218],"achieves":[221],"promising":[222],"detecting":[225],"both":[226],"non-occluded":[227],"pedestrians,":[230],"heavily":[232],"ones.":[234]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
