{"id":"https://openalex.org/W4402351507","doi":"https://doi.org/10.1109/ijcnn60899.2024.10649985","title":"Location IoU: A New Evaluation and Loss for Bounding Box Regression in Object Detection","display_name":"Location IoU: A New Evaluation and Loss for Bounding Box Regression in Object Detection","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402351507","doi":"https://doi.org/10.1109/ijcnn60899.2024.10649985"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10649985","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10649985","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","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/A5100454255","display_name":"Yang Lu","orcid":"https://orcid.org/0000-0002-3580-3255"},"institutions":[{"id":"https://openalex.org/I136765683","display_name":"Tianjin University of Technology","ror":"https://ror.org/00zbe0w13","country_code":"CN","type":"education","lineage":["https://openalex.org/I136765683"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lu Yang","raw_affiliation_strings":["Tianjin University of Technology,Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control,Tianjin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University of Technology,Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control,Tianjin,China","institution_ids":["https://openalex.org/I136765683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101871787","display_name":"Kai Zhang","orcid":"https://orcid.org/0000-0002-5826-3765"},"institutions":[{"id":"https://openalex.org/I136765683","display_name":"Tianjin University of Technology","ror":"https://ror.org/00zbe0w13","country_code":"CN","type":"education","lineage":["https://openalex.org/I136765683"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Zhang","raw_affiliation_strings":["Tianjin University of Technology,Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control,Tianjin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University of Technology,Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control,Tianjin,China","institution_ids":["https://openalex.org/I136765683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079197142","display_name":"Jiaqi Liu","orcid":"https://orcid.org/0000-0002-7402-1731"},"institutions":[{"id":"https://openalex.org/I136765683","display_name":"Tianjin University of Technology","ror":"https://ror.org/00zbe0w13","country_code":"CN","type":"education","lineage":["https://openalex.org/I136765683"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaqi Liu","raw_affiliation_strings":["Tianjin University of Technology,Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control,Tianjin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University of Technology,Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control,Tianjin,China","institution_ids":["https://openalex.org/I136765683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100786077","display_name":"Chongke Bi","orcid":"https://orcid.org/0000-0002-4324-8028"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chongke Bi","raw_affiliation_strings":["Tianjin University,College of Intelligence and Computing,Tianjin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University,College of Intelligence and Computing,Tianjin,China","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3147,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.85441838,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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":0.9998000264167786,"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":0.996999979019165,"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":0.9955999851226807,"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/minimum-bounding-box","display_name":"Minimum bounding box","score":0.8269540667533875},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7198267579078674},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.671295702457428},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5896526575088501},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5420956611633301},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5130339860916138},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.48227575421333313},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.429345965385437},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.40067607164382935},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.26194941997528076},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16264066100120544},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.11409351229667664}],"concepts":[{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.8269540667533875},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7198267579078674},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.671295702457428},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5896526575088501},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5420956611633301},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5130339860916138},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.48227575421333313},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.429345965385437},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40067607164382935},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.26194941997528076},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16264066100120544},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.11409351229667664}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10649985","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10649985","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1964357740","https://openalex.org/W2031489346","https://openalex.org/W2129987527","https://openalex.org/W2186222003","https://openalex.org/W2193145675","https://openalex.org/W2340897893","https://openalex.org/W2504335775","https://openalex.org/W2585439946","https://openalex.org/W2737258237","https://openalex.org/W2743627947","https://openalex.org/W2934198733","https://openalex.org/W2952122856","https://openalex.org/W2962677013","https://openalex.org/W2962766617","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2963179609","https://openalex.org/W2963299996","https://openalex.org/W2965745049","https://openalex.org/W2969875432","https://openalex.org/W2970738028","https://openalex.org/W2982770724","https://openalex.org/W2989604896","https://openalex.org/W2989676862","https://openalex.org/W2997747012","https://openalex.org/W3034427487","https://openalex.org/W3034528588","https://openalex.org/W3034959114","https://openalex.org/W3034971973","https://openalex.org/W3035219584","https://openalex.org/W3035257046","https://openalex.org/W3106250896","https://openalex.org/W3122173535","https://openalex.org/W3214740560","https://openalex.org/W4221138453","https://openalex.org/W4281790833","https://openalex.org/W4295331127","https://openalex.org/W4391640632","https://openalex.org/W6631313198","https://openalex.org/W6679461745","https://openalex.org/W6753494528","https://openalex.org/W6803209311","https://openalex.org/W6838547440"],"related_works":["https://openalex.org/W4237171675","https://openalex.org/W3036286480","https://openalex.org/W4287027631","https://openalex.org/W3192357901","https://openalex.org/W2387360586","https://openalex.org/W2952736415","https://openalex.org/W3209723314","https://openalex.org/W3205398323","https://openalex.org/W2883297582","https://openalex.org/W4390524233"],"abstract_inverted_index":{"In":[0,91],"the":[1,21,37,81,111,115,120,155,161,165,174,180],"field":[2],"of":[3,32,83,89,114,133,170,176,182],"object":[4,183],"detection":[5,184],"bounding":[6,28,48],"box":[7],"regression,":[8],"IoU":[9],"(Intersection":[10],"over":[11],"Union)":[12],"is":[13,35,44,102],"a":[14,94,125],"commonly":[15],"used":[16,118],"evaluation":[17,51,96],"metric":[18],"for":[19,67],"measuring":[20],"overlap":[22],"between":[23,47],"predicted":[24],"and":[25,64,86,123,144,151,158],"ground":[26],"truth":[27],"boxes.":[29,49],"One":[30],"limitation":[31],"IoU,":[33],"however,":[34],"that":[36,140],"gradient":[38,127],"goes":[39],"to":[40,56,77,104,129,131],"zero":[41],"when":[42,117],"there":[43],"no":[45],"intersection":[46,116],"Recent":[50],"metrics":[52],"have":[53],"been":[54],"developed":[55],"overcome":[57],"this":[58,92,171],"problem":[59],"by":[60],"incorporating":[61],"penalty":[62],"terms":[63],"other":[65],"techniques":[66],"improving":[68,179],"IoU.":[69],"Despite":[70],"these":[71,106],"advances,":[72],"existing":[73],"methods":[74],"still":[75],"suffer":[76],"some":[78],"degree":[79],"from":[80],"problems":[82],"small":[84],"gradients":[85],"slow":[87],"rate":[88],"convergence.":[90],"paper,":[93],"new":[95],"method":[97],"named":[98],"LIoU":[99,177],"(Location":[100],"IoU)":[101],"proposed":[103],"address":[105],"issues.":[107],"It":[108],"can":[109],"maximize":[110],"shared":[112],"area":[113],"as":[119],"loss":[121],"function":[122],"incorporate":[124],"variable":[126],"parameter":[128],"fit":[130],"datasets":[132],"different":[134],"sizes.":[135],"The":[136,168],"experimental":[137],"results":[138,169],"indicate":[139],"we":[141],"achieve":[142],"0.27%":[143],"3.48%":[145],"accuracy":[146],"improvements":[147],"respectively":[148],"in":[149,160,178],"SSD":[150],"YOLOv5":[152,162],"network":[153,163],"on":[154,164],"VOC":[156],"dataset,":[157],"2.23%":[159],"COCO":[166],"dataset.":[167],"study":[172],"highlight":[173],"effectiveness":[175],"performance":[181],"models.":[185]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
