{"id":"https://openalex.org/W3038556141","doi":"https://doi.org/10.1109/tnnls.2020.3002583","title":"IncDet: In Defense of Elastic Weight Consolidation for Incremental Object Detection","display_name":"IncDet: In Defense of Elastic Weight Consolidation for Incremental Object Detection","publication_year":2020,"publication_date":"2020-06-29","ids":{"openalex":"https://openalex.org/W3038556141","doi":"https://doi.org/10.1109/tnnls.2020.3002583","mag":"3038556141","pmid":"https://pubmed.ncbi.nlm.nih.gov/32598286"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2020.3002583","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2020.3002583","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://discovery.ucl.ac.uk/10103165/1/TNNLS-2019-P-11867.R2-UCL.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101831985","display_name":"Liyang Liu","orcid":"https://orcid.org/0000-0002-6868-319X"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Liyang Liu","raw_affiliation_strings":["Shenzhen Key Laboratory of Information Science and Technology/Shenzhen Engineering Laboratory of IS.&DCP., Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Key Laboratory of Information Science and Technology/Shenzhen Engineering Laboratory of IS.&DCP., Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054299179","display_name":"Zhanghui Kuang","orcid":"https://orcid.org/0000-0002-9102-5152"},"institutions":[{"id":"https://openalex.org/I4210128910","display_name":"Group Sense (China)","ror":"https://ror.org/036wd5777","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210128910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhanghui Kuang","raw_affiliation_strings":["SenseTime Research, Hong Kong"],"affiliations":[{"raw_affiliation_string":"SenseTime Research, Hong Kong","institution_ids":["https://openalex.org/I4210128910"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001599513","display_name":"Yimin Chen","orcid":"https://orcid.org/0000-0003-1976-6041"},"institutions":[{"id":"https://openalex.org/I4210128910","display_name":"Group Sense (China)","ror":"https://ror.org/036wd5777","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210128910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yimin Chen","raw_affiliation_strings":["SenseTime Research, Hong Kong"],"affiliations":[{"raw_affiliation_string":"SenseTime Research, Hong Kong","institution_ids":["https://openalex.org/I4210128910"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079361172","display_name":"Jing\u2010Hao Xue","orcid":"https://orcid.org/0000-0003-1174-610X"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jing-Hao Xue","raw_affiliation_strings":["University College London, London, U.K"],"affiliations":[{"raw_affiliation_string":"University College London, London, U.K","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026184280","display_name":"Wenming Yang","orcid":"https://orcid.org/0000-0002-2506-1286"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenming Yang","raw_affiliation_strings":["Shenzhen Key Laboratory of Information Science and Technology/Shenzhen Engineering Laboratory of IS.&DCP., Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Key Laboratory of Information Science and Technology/Shenzhen Engineering Laboratory of IS.&DCP., Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057842914","display_name":"Wei Zhang","orcid":"https://orcid.org/0000-0002-8415-1062"},"institutions":[{"id":"https://openalex.org/I4210128910","display_name":"Group Sense (China)","ror":"https://ror.org/036wd5777","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210128910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wayne Zhang","raw_affiliation_strings":["SenseTime Research, Hong Kong"],"affiliations":[{"raw_affiliation_string":"SenseTime Research, Hong Kong","institution_ids":["https://openalex.org/I4210128910"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101831985"],"corresponding_institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":4.2188,"has_fulltext":true,"cited_by_count":75,"citation_normalized_percentile":{"value":0.95375943,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"32","issue":"6","first_page":"2306","last_page":"2319"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9998000264167786,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.7485183477401733},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6639503240585327},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6068978309631348},{"id":"https://openalex.org/keywords/quadratic-equation","display_name":"Quadratic equation","score":0.5880135297775269},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.47406667470932007},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.44824039936065674},{"id":"https://openalex.org/keywords/consolidation","display_name":"Consolidation (business)","score":0.43434906005859375},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43131470680236816},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.415963739156723},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3348744511604309},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33138298988342285},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.28317102789878845},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.08424776792526245}],"concepts":[{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.7485183477401733},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6639503240585327},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6068978309631348},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.5880135297775269},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.47406667470932007},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.44824039936065674},{"id":"https://openalex.org/C2776014549","wikidata":"https://www.wikidata.org/wiki/Q3050847","display_name":"Consolidation (business)","level":2,"score":0.43434906005859375},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43131470680236816},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.415963739156723},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3348744511604309},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33138298988342285},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28317102789878845},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.08424776792526245},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tnnls.2020.3002583","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2020.3002583","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:32598286","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/32598286","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 neural networks and learning systems","raw_type":null},{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:10103165","is_oa":true,"landing_page_url":"https://discovery.ucl.ac.uk/id/eprint/10103165/","pdf_url":"https://discovery.ucl.ac.uk/10103165/1/TNNLS-2019-P-11867.R2-UCL.pdf","source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"   IEEE Transactions on Neural Networks and Learning Systems       (2020)     (In press).  ","raw_type":"Article"}],"best_oa_location":{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:10103165","is_oa":true,"landing_page_url":"https://discovery.ucl.ac.uk/id/eprint/10103165/","pdf_url":"https://discovery.ucl.ac.uk/10103165/1/TNNLS-2019-P-11867.R2-UCL.pdf","source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"   IEEE Transactions on Neural Networks and Learning Systems       (2020)     (In press).  ","raw_type":"Article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1285054254","display_name":null,"funder_award_id":"JCYJ20170817161845824","funder_id":"https://openalex.org/F4320335972","funder_display_name":"Special Foundation for the Development of Strategic Emerging Industries of Shenzhen"},{"id":"https://openalex.org/G8142528893","display_name":null,"funder_award_id":"2016YFB0101001","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G915989819","display_name":null,"funder_award_id":"2020A1515010711","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320335972","display_name":"Special Foundation for the Development of Strategic Emerging Industries of Shenzhen","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3038556141.pdf","grobid_xml":"https://content.openalex.org/works/W3038556141.grobid-xml"},"referenced_works_count":92,"referenced_works":["https://openalex.org/W7746136","https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1549777868","https://openalex.org/W1682403713","https://openalex.org/W1815076433","https://openalex.org/W1821462560","https://openalex.org/W1836465849","https://openalex.org/W1861492603","https://openalex.org/W1973264045","https://openalex.org/W1985602045","https://openalex.org/W2021150359","https://openalex.org/W2031489346","https://openalex.org/W2048868165","https://openalex.org/W2079057609","https://openalex.org/W2088049833","https://openalex.org/W2088220893","https://openalex.org/W2096987757","https://openalex.org/W2102605133","https://openalex.org/W2108598243","https://openalex.org/W2108807072","https://openalex.org/W2109255472","https://openalex.org/W2109526843","https://openalex.org/W2111051539","https://openalex.org/W2117287331","https://openalex.org/W2160512933","https://openalex.org/W2194775991","https://openalex.org/W2277195237","https://openalex.org/W2287924575","https://openalex.org/W2426267443","https://openalex.org/W2473930607","https://openalex.org/W2560647685","https://openalex.org/W2565639579","https://openalex.org/W2591909298","https://openalex.org/W2609002182","https://openalex.org/W2613718673","https://openalex.org/W2622263826","https://openalex.org/W2737492962","https://openalex.org/W2738226240","https://openalex.org/W2765101016","https://openalex.org/W2786446225","https://openalex.org/W2803552920","https://openalex.org/W2804746922","https://openalex.org/W2890126432","https://openalex.org/W2899505139","https://openalex.org/W2901367914","https://openalex.org/W2962966271","https://openalex.org/W2963003887","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2963311299","https://openalex.org/W2963351448","https://openalex.org/W2963540014","https://openalex.org/W2963559848","https://openalex.org/W2963577698","https://openalex.org/W2963588172","https://openalex.org/W2963785012","https://openalex.org/W2963876278","https://openalex.org/W2966730026","https://openalex.org/W2970971581","https://openalex.org/W2983156430","https://openalex.org/W2984276908","https://openalex.org/W3013325675","https://openalex.org/W3106250896","https://openalex.org/W3121480429","https://openalex.org/W4289286873","https://openalex.org/W4295312788","https://openalex.org/W4301163820","https://openalex.org/W4319988532","https://openalex.org/W6600313631","https://openalex.org/W6620707391","https://openalex.org/W6632923127","https://openalex.org/W6638523607","https://openalex.org/W6638545294","https://openalex.org/W6638667902","https://openalex.org/W6639102338","https://openalex.org/W6676485797","https://openalex.org/W6737135848","https://openalex.org/W6738602802","https://openalex.org/W6739622702","https://openalex.org/W6741217325","https://openalex.org/W6742852309","https://openalex.org/W6745121187","https://openalex.org/W6746266179","https://openalex.org/W6748649680","https://openalex.org/W6751689095","https://openalex.org/W6752540598","https://openalex.org/W6756063162","https://openalex.org/W6766978945","https://openalex.org/W6785652829","https://openalex.org/W6788995615","https://openalex.org/W6849896277"],"related_works":["https://openalex.org/W4289718052","https://openalex.org/W2164121020","https://openalex.org/W2145559838","https://openalex.org/W2905319430","https://openalex.org/W3116498279","https://openalex.org/W4287549553","https://openalex.org/W4310285384","https://openalex.org/W3183027292","https://openalex.org/W4248896073","https://openalex.org/W4299904075"],"abstract_inverted_index":{"Elastic":[0],"weight":[1,49],"consolidation":[2],"(EWC)":[3],"has":[4],"been":[5],"successfully":[6],"applied":[7,102],"for":[8,50,79,177],"general":[9,206],"incremental":[10,80,104,208],"learning":[11],"to":[12,28,46,92,103,139,159,175,197,240],"overcome":[13],"the":[14,24,35,54,107,131,151,156,178,193,231,235,241,253,269],"catastrophic":[15,63],"forgetting":[16,64],"issue.":[17],"It":[18],"adaptively":[19],"constrains":[20],"each":[21],"parameter":[22],"of":[23,109,121,168,180,192,229,244,268],"new":[25,41,114,146,172,266],"model":[26,37],"not":[27],"deviate":[29],"much":[30],"from":[31,62,199],"its":[32,47,223],"counterpart":[33],"in":[34,68,113,124,135],"old":[36,51,110,122,144,169,181],"during":[38],"fine-tuning":[39],"on":[40,150,171,247,252],"class":[42,111,115,182],"data":[43,173,258],"sets,":[44],"according":[45],"importance":[48],"tasks.":[52],"However,":[53],"previous":[55],"study":[56],"demonstrates":[57],"that":[58,261],"it":[59,214],"still":[60],"suffers":[61],"when":[65,142],"directly":[66],"used":[67],"object":[69,81,209],"detection.":[70],"In":[71,227],"this":[72],"article,":[73],"we":[74,88,154,203],"show":[75,260],"EWC":[76,98,118,136],"is":[77],"effective":[78],"detection":[82,210],"if":[83,100],"with":[84,238],"critical":[85],"adaptations.":[86],"First,":[87],"conduct":[89],"controlled":[90],"experiments":[91],"identify":[93],"two":[94],"core":[95],"issues":[96],"why":[97],"fails":[99],"trivially":[101],"detection:":[105],"1)":[106,163],"absence":[108,179],"annotations":[112,167,183],"images":[116,126],"makes":[117],"misclassify":[119],"objects":[120],"classes":[123,170],"these":[125,161],"as":[127],"background":[128],"and":[129,145,184,212,219,225,256],"2)":[130,185],"quadratic":[132,195],"regularization":[133,190],"loss":[134,196],"easily":[137],"leads":[138],"gradient":[140],"explosion":[141],"balancing":[143],"classes.":[147],"Then,":[148],"based":[149],"abovementioned":[152],"findings,":[153],"propose":[155,204],"corresponding":[157],"solutions":[158],"tackle":[160],"issues:":[162],"utilize":[164],"pseudobounding":[165],"box":[166],"sets":[174,259],"compensate":[176],"adopt":[186],"a":[187,205,265],"novel":[188],"Huber":[189],"instead":[191],"original":[194],"prevent":[198],"unstable":[200],"training.":[201],"Finally,":[202],"EWC-based":[207],"framework":[211],"implement":[213],"under":[215],"both":[216],"Fast":[217],"R-CNN":[218],"Faster":[220],"R-CNN,":[221],"showing":[222],"flexibility":[224],"versatility.":[226],"terms":[228],"either":[230],"final":[232],"performance":[233,236],"or":[234],"drop":[237],"respect":[239],"upper":[242],"bound":[243],"joint":[245],"training":[246],"all":[248],"seen":[249],"classes,":[250],"evaluations":[251],"PASCAL":[254],"VOC":[255],"COCO":[257],"our":[262],"method":[263],"achieves":[264],"state":[267],"art.":[270]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":19},{"year":2023,"cited_by_count":19},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}