{"id":"https://openalex.org/W2989676862","doi":"https://doi.org/10.1109/tpami.2019.2956516","title":"Cascade R-CNN: High Quality Object Detection and Instance Segmentation","display_name":"Cascade R-CNN: High Quality Object Detection and Instance Segmentation","publication_year":2019,"publication_date":"2019-11-28","ids":{"openalex":"https://openalex.org/W2989676862","doi":"https://doi.org/10.1109/tpami.2019.2956516","mag":"2989676862","pmid":"https://pubmed.ncbi.nlm.nih.gov/31794388"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2019.2956516","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2019.2956516","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5103259598","display_name":"Zhaowei Cai","orcid":"https://orcid.org/0000-0003-2023-7761"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhaowei Cai","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, CA, USA","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043325212","display_name":"Nuno Vasconcelos","orcid":"https://orcid.org/0000-0002-9024-4302"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nuno Vasconcelos","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, CA, USA","institution_ids":["https://openalex.org/I36258959"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I36258959"],"apc_list":null,"apc_paid":null,"fwci":54.4551,"has_fulltext":false,"cited_by_count":1848,"citation_normalized_percentile":{"value":0.99933449,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"43","issue":"5","first_page":"1483","last_page":"1498"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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":1.0,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.995199978351593,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9868000149726868,"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/overfitting","display_name":"Overfitting","score":0.8677414655685425},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.7683537006378174},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7428779602050781},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7070664167404175},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6356496810913086},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6229197382926941},{"id":"https://openalex.org/keywords/cascade","display_name":"Cascade","score":0.6013697385787964},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5763645172119141},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.5309861302375793},{"id":"https://openalex.org/keywords/viola\u2013jones-object-detection-framework","display_name":"Viola\u2013Jones object detection framework","score":0.47662246227264404},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.47217315435409546},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.43480274081230164},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.38482770323753357},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.18354684114456177},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.15912845730781555},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0819997787475586}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8677414655685425},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.7683537006378174},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7428779602050781},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7070664167404175},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6356496810913086},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6229197382926941},{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.6013697385787964},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5763645172119141},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.5309861302375793},{"id":"https://openalex.org/C182521987","wikidata":"https://www.wikidata.org/wiki/Q2493877","display_name":"Viola\u2013Jones object detection framework","level":5,"score":0.47662246227264404},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.47217315435409546},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.43480274081230164},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38482770323753357},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.18354684114456177},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.15912845730781555},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0819997787475586},{"id":"https://openalex.org/C42360764","wikidata":"https://www.wikidata.org/wiki/Q83588","display_name":"Chemical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"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":2,"locations":[{"id":"doi:10.1109/tpami.2019.2956516","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2019.2956516","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:31794388","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31794388","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8399999737739563,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":87,"referenced_works":["https://openalex.org/W167016754","https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1686810756","https://openalex.org/W1689909837","https://openalex.org/W1836465849","https://openalex.org/W1861492603","https://openalex.org/W1932624639","https://openalex.org/W1934410531","https://openalex.org/W1988790447","https://openalex.org/W2031454541","https://openalex.org/W2031489346","https://openalex.org/W2088049833","https://openalex.org/W2090530238","https://openalex.org/W2102605133","https://openalex.org/W2117539524","https://openalex.org/W2119821739","https://openalex.org/W2120396754","https://openalex.org/W2135825553","https://openalex.org/W2136000821","https://openalex.org/W2138406903","https://openalex.org/W2150066425","https://openalex.org/W2155893237","https://openalex.org/W2157285372","https://openalex.org/W2168356304","https://openalex.org/W2179352600","https://openalex.org/W2194775991","https://openalex.org/W2216125271","https://openalex.org/W2407521645","https://openalex.org/W2490270993","https://openalex.org/W2549139847","https://openalex.org/W2557728737","https://openalex.org/W2565639579","https://openalex.org/W2594507094","https://openalex.org/W2601564443","https://openalex.org/W2613718673","https://openalex.org/W2768489488","https://openalex.org/W2779991293","https://openalex.org/W2793025567","https://openalex.org/W2886335102","https://openalex.org/W2886904239","https://openalex.org/W2894651257","https://openalex.org/W2896540732","https://openalex.org/W2950800384","https://openalex.org/W2962835968","https://openalex.org/W2963016543","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2963296245","https://openalex.org/W2963351448","https://openalex.org/W2963418361","https://openalex.org/W2963516811","https://openalex.org/W2963549237","https://openalex.org/W2963566548","https://openalex.org/W2963674932","https://openalex.org/W2963786238","https://openalex.org/W2963857746","https://openalex.org/W2963873508","https://openalex.org/W2964080601","https://openalex.org/W2964121718","https://openalex.org/W2964241181","https://openalex.org/W2964297960","https://openalex.org/W2991391304","https://openalex.org/W3012183369","https://openalex.org/W3012573144","https://openalex.org/W3097096317","https://openalex.org/W3106250896","https://openalex.org/W4239510810","https://openalex.org/W4248437541","https://openalex.org/W6606837198","https://openalex.org/W6620707391","https://openalex.org/W6637373629","https://openalex.org/W6638667902","https://openalex.org/W6639102338","https://openalex.org/W6648088351","https://openalex.org/W6676338569","https://openalex.org/W6703941868","https://openalex.org/W6714138976","https://openalex.org/W6717137822","https://openalex.org/W6722946945","https://openalex.org/W6749684117","https://openalex.org/W6749954789","https://openalex.org/W6753494528","https://openalex.org/W6753610190","https://openalex.org/W6755158094","https://openalex.org/W6755578354","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W3160582076","https://openalex.org/W3204852000","https://openalex.org/W2965402078","https://openalex.org/W2963251476","https://openalex.org/W4297797959","https://openalex.org/W4297491714","https://openalex.org/W4256727525","https://openalex.org/W4387272257","https://openalex.org/W3108847140","https://openalex.org/W4200612475"],"abstract_inverted_index":{"In":[0],"object":[1,74,175],"detection,":[2],"the":[3,26,77,103,112,152,163,184,196],"intersection":[4],"over":[5,195],"union":[6],"(IoU)":[7],"threshold":[8,16,29],"is":[9,91,137,187],"frequently":[10,39],"used":[11,17,28],"to":[12,18,33,55,93,141,189],"define":[13],"positives/negatives.":[14],"The":[15,97,134],"train":[19],"a":[20,82,106,121],"detector":[21,68,107],"defines":[22],"its":[23],"quality.":[24],"While":[25],"commonly":[27],"of":[30,46,81,84,105,125,151],"0.5":[31],"leads":[32],"noisy":[34],"(low-quality)":[35],"detections,":[36],"detection":[37,48,75,170],"performance":[38,161],"degrades":[40],"for":[41,59,111,128],"larger":[42],"thresholds.":[43],"This":[44,114],"paradox":[45],"high-quality":[47,169],"has":[49],"two":[50],"causes:":[51],"1)":[52],"overfitting,":[53],"due":[54],"vanishing":[56],"positive":[57,122],"samples":[58],"large":[60],"thresholds,":[61,90],"and":[62,69,131,147,166,173,181],"2)":[63],"inference-time":[64],"quality":[65,143],"mismatch":[66],"between":[67,145],"test":[70],"hypotheses.":[71],"A":[72],"multi-stage":[73],"architecture,":[76],"Cascade":[78,153,185],"R-CNN,":[79],"composed":[80],"sequence":[83],"detectors":[85,98,130],"trained":[86,100],"with":[87,192],"increasing":[88],"IoU":[89],"proposed":[92],"address":[94],"these":[95],"problems.":[96],"are":[99],"sequentially,":[101],"using":[102],"output":[104],"as":[108],"training":[109,123],"set":[110,124],"next.":[113],"resampling":[115],"progressively":[116],"improves":[117,168],"hypotheses":[118,146],"quality,":[119],"guaranteeing":[120],"equivalent":[126],"size":[127],"all":[129],"minimizing":[132],"overfitting.":[133],"same":[135],"cascade":[136],"applied":[138],"at":[139],"inference,":[140],"eliminate":[142],"mismatches":[144],"detectors.":[148],"An":[149],"implementation":[150],"R-CNN":[154,186],"without":[155],"bells":[156],"or":[157],"whistles":[158],"achieves":[159],"state-of-the-art":[160],"on":[162,171],"COCO":[164],"dataset,":[165],"significantly":[167],"generic":[172],"specific":[174],"datasets,":[176],"including":[177],"VOC,":[178],"KITTI,":[179],"CityPerson,":[180],"WiderFace.":[182],"Finally,":[183],"generalized":[188],"instance":[190],"segmentation,":[191],"nontrivial":[193],"improvements":[194],"Mask":[197],"R-CNN.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":174},{"year":2025,"cited_by_count":475},{"year":2024,"cited_by_count":381},{"year":2023,"cited_by_count":337},{"year":2022,"cited_by_count":222},{"year":2021,"cited_by_count":180},{"year":2020,"cited_by_count":74},{"year":2019,"cited_by_count":5}],"updated_date":"2026-07-31T08:31:51.225901","created_date":"2019-12-05T00:00:00"}