{"id":"https://openalex.org/W4210768747","doi":"https://doi.org/10.1145/3472393","title":"RD-IOD: Two-Level Residual-Distillation-Based Triple-Network for Incremental Object Detection","display_name":"RD-IOD: Two-Level Residual-Distillation-Based Triple-Network for Incremental Object Detection","publication_year":2022,"publication_date":"2022-01-27","ids":{"openalex":"https://openalex.org/W4210768747","doi":"https://doi.org/10.1145/3472393"},"language":"en","primary_location":{"id":"doi:10.1145/3472393","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3472393","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","raw_type":"journal-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/A5016775929","display_name":"Dongbao Yang","orcid":"https://orcid.org/0000-0001-8628-411X"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dongbao Yang","raw_affiliation_strings":["Chinese Academy of Sciences and University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences and University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016175345","display_name":"Yu Zhou","orcid":"https://orcid.org/0000-0003-4188-9953"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Zhou","raw_affiliation_strings":["Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100651614","display_name":"Wei Shi","orcid":"https://orcid.org/0000-0002-3071-8350"},"institutions":[{"id":"https://openalex.org/I67031392","display_name":"Carleton University","ror":"https://ror.org/02qtvee93","country_code":"CA","type":"education","lineage":["https://openalex.org/I67031392"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Wei Shi","raw_affiliation_strings":["Carleton University, Ottawa, Canada"],"affiliations":[{"raw_affiliation_string":"Carleton University, Ottawa, Canada","institution_ids":["https://openalex.org/I67031392"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002436544","display_name":"Dayan Wu","orcid":"https://orcid.org/0000-0002-8604-7226"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dayan Wu","raw_affiliation_strings":["Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100442321","display_name":"Weiping Wang","orcid":"https://orcid.org/0000-0002-8618-4992"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiping Wang","raw_affiliation_strings":["Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5016775929"],"corresponding_institution_ids":["https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":2.4504,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.90204641,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"18","issue":"1","first_page":"1","last_page":"23"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9995999932289124,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9983999729156494,"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/computer-science","display_name":"Computer science","score":0.8557833433151245},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.7172861695289612},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6604891419410706},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6213605403900146},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5946269035339355},{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.5814254283905029},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.573108971118927},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5294154286384583},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5290704369544983},{"id":"https://openalex.org/keywords/learning-object","display_name":"Learning object","score":0.5032312273979187},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.48270726203918457},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4266204237937927},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1606833040714264}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8557833433151245},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.7172861695289612},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6604891419410706},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6213605403900146},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5946269035339355},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.5814254283905029},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.573108971118927},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5294154286384583},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5290704369544983},{"id":"https://openalex.org/C2779542340","wikidata":"https://www.wikidata.org/wiki/Q1062461","display_name":"Learning object","level":2,"score":0.5032312273979187},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.48270726203918457},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4266204237937927},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1606833040714264},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3472393","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3472393","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.49000000953674316,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"},{"score":0.46000000834465027,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G2756658477","display_name":null,"funder_award_id":"Z191100007119002","funder_id":"https://openalex.org/F4320325902","funder_display_name":"Beijing Municipal Science and Technology Commission"},{"id":"https://openalex.org/G8741921880","display_name":null,"funder_award_id":"62006221","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320325902","display_name":"Beijing Municipal Science and Technology Commission","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W7746136","https://openalex.org/W102110531","https://openalex.org/W1536680647","https://openalex.org/W1821462560","https://openalex.org/W1861492603","https://openalex.org/W1991367009","https://openalex.org/W2015563892","https://openalex.org/W2031489346","https://openalex.org/W2060277733","https://openalex.org/W2103753221","https://openalex.org/W2113839990","https://openalex.org/W2166344886","https://openalex.org/W2193145675","https://openalex.org/W2194775991","https://openalex.org/W2473930607","https://openalex.org/W2474280151","https://openalex.org/W2554616628","https://openalex.org/W2560647685","https://openalex.org/W2605911906","https://openalex.org/W2904531787","https://openalex.org/W2948734064","https://openalex.org/W2950557191","https://openalex.org/W2962966271","https://openalex.org/W2963018216","https://openalex.org/W2963351448","https://openalex.org/W2963588172","https://openalex.org/W2964067969","https://openalex.org/W2964189064","https://openalex.org/W2964241181","https://openalex.org/W2966730026","https://openalex.org/W2977932430","https://openalex.org/W2983156430","https://openalex.org/W2984276908","https://openalex.org/W2990154684","https://openalex.org/W2997907976","https://openalex.org/W3003861315","https://openalex.org/W3013325675","https://openalex.org/W3027134841","https://openalex.org/W3034381931","https://openalex.org/W3034447740","https://openalex.org/W3039204154","https://openalex.org/W3103800629","https://openalex.org/W3106250896","https://openalex.org/W3161907096","https://openalex.org/W3178307467","https://openalex.org/W4287812705","https://openalex.org/W4287827901","https://openalex.org/W6638523607","https://openalex.org/W6720926796","https://openalex.org/W6760424586","https://openalex.org/W6774434044","https://openalex.org/W6776700526"],"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/W2974871044"],"abstract_inverted_index":{"As":[0],"a":[1,13,75,92,113,166,181,194,209,225,234,239],"basic":[2],"component":[3],"in":[4,32,159,189,200],"multimedia":[5],"applications,":[6],"object":[7,23,35,68],"detectors":[8,36],"are":[9,19,30],"generally":[10],"trained":[11,31,151],"on":[12,38,49,67,81,88,95,124,156,197,213,245],"fixed":[14],"set":[15],"of":[16,91,120,141,179,233,261,267],"classes":[17,24,51,126,158],"that":[18,250],"pre-defined.":[20],"However,":[21],"new":[22,50,103,125,144,157,262],"often":[25],"emerge":[26],"after":[27],"the":[28,53,63,89,107,118,121,129,136,139,146,153,160,174,186,198,214,220,231,251,265],"models":[29],"practice.":[33],"Modern":[34],"based":[37,94],"Convolutional":[39],"Neural":[40],"Networks":[41],"(CNN)":[42],"suffer":[43],"from":[44,102],"catastrophic":[45,268],"forgetting":[46,269],"when":[47],"fine-tuning":[48],"without":[52],"original":[54,108,187],"training":[55,175,227],"data.":[56],"Therefore,":[57],"it":[58],"is":[59,149,170,270,274],"critical":[60],"to":[61,116,172,229,257],"improve":[62],"incremental":[64,122,154,161],"learning":[65,79,101,119,162,232],"capability":[66],"detection.":[69],"In":[70,164],"this":[71],"article,":[72],"we":[73,105,223],"propose":[74],"novel":[76],"Residual-Distillation-based":[77],"Incremental":[78],"method":[80,253],"Object":[82],"Detection":[83],"(RD-IOD).":[84],"Our":[85,272],"approach":[86],"rests":[87],"creation":[90],"triple-network":[93],"Faster":[96],"R-CNN.":[97],"To":[98,133,217],"enable":[99],"continuous":[100],"classes,":[104,145,263],"use":[106],"model":[109,115,123,148,155,188],"as":[110,112],"well":[111,218],"residual":[114,147,195],"guide":[117,173,230],"while":[127],"maintaining":[128],"previous":[130],"learned":[131,221],"knowledge.":[132],"better":[134],"maintain":[135],"discrimination":[137],"between":[138],"features":[140,199],"old":[142],"and":[143,204,207,238,247,264],"jointly":[150],"with":[152,193],"procedure.":[163],"addition,":[165],"two-level":[167],"distillation":[168,183,196,212],"scheme":[169],"designed":[171],"process,":[176],"which":[177],"consists":[178],"(1)":[180],"general":[182],"for":[184],"imitating":[185],"feature":[190],"space":[191],"along":[192],"both":[201],"image":[202],"level":[203],"instance":[205],"level,":[206],"(2)":[208],"joint":[210],"classification":[211],"output":[215],"layers.":[216],"preserve":[219],"knowledge,":[222],"design":[224],"2-threshold":[226],"strategy":[228],"Region":[235],"Proposal":[236],"Network":[237],"detection":[240],"head.":[241],"Extensive":[242],"experiments":[243],"conducted":[244],"VOC2007":[246],"COCO":[248],"demonstrate":[249],"proposed":[252],"can":[254],"effectively":[255],"learn":[256],"incrementally":[258],"detect":[259],"objects":[260],"problem":[266],"mitigated.":[271],"code":[273],"available":[275],"at":[276],"https://github.com/yangdb/RD-IOD.":[277]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
