{"id":"https://openalex.org/W3183430956","doi":"https://doi.org/10.1109/tpami.2022.3164083","title":"Contextual Transformer Networks for Visual Recognition","display_name":"Contextual Transformer Networks for Visual Recognition","publication_year":2022,"publication_date":"2022-04-01","ids":{"openalex":"https://openalex.org/W3183430956","doi":"https://doi.org/10.1109/tpami.2022.3164083","mag":"3183430956","pmid":"https://pubmed.ncbi.nlm.nih.gov/35363608"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2022.3164083","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3164083","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/A5041154840","display_name":"Yehao Li","orcid":"https://orcid.org/0000-0002-9603-1113"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yehao Li","raw_affiliation_strings":["JD Explore Academy, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-9603-1113","affiliations":[{"raw_affiliation_string":"JD Explore Academy, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088760097","display_name":"Ting Yao","orcid":"https://orcid.org/0000-0001-7587-101X"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ting Yao","raw_affiliation_strings":["JD Explore Academy, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7587-101X","affiliations":[{"raw_affiliation_string":"JD Explore Academy, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085403640","display_name":"Yingwei Pan","orcid":"https://orcid.org/0000-0002-4344-8898"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingwei Pan","raw_affiliation_strings":["JD Explore Academy, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4344-8898","affiliations":[{"raw_affiliation_string":"JD Explore Academy, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017597537","display_name":"Tao Mei","orcid":"https://orcid.org/0000-0003-2497-7732"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Mei","raw_affiliation_strings":["JD Explore Academy, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2497-7732","affiliations":[{"raw_affiliation_string":"JD Explore Academy, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5041154840"],"corresponding_institution_ids":["https://openalex.org/I4210103986"],"apc_list":null,"apc_paid":null,"fwci":65.5739,"has_fulltext":false,"cited_by_count":695,"citation_normalized_percentile":{"value":0.99958059,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"45","issue":"2","first_page":"1489","last_page":"1500"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9994000196456909,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9993000030517578,"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":0.7723863124847412},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5836694836616516},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5722732543945312},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4989347457885742},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.46343666315078735},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4507385492324829},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3798432946205139},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09870371222496033}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7723863124847412},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5836694836616516},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5722732543945312},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4989347457885742},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.46343666315078735},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4507385492324829},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3798432946205139},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09870371222496033},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2022.3164083","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3164083","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:35363608","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35363608","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":0.5799999833106995,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":98,"referenced_works":["https://openalex.org/W4919037","https://openalex.org/W603908379","https://openalex.org/W639708223","https://openalex.org/W1686810756","https://openalex.org/W1861492603","https://openalex.org/W2081293863","https://openalex.org/W2095705004","https://openalex.org/W2097117768","https://openalex.org/W2108598243","https://openalex.org/W2112796928","https://openalex.org/W2125215748","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2507296351","https://openalex.org/W2518108298","https://openalex.org/W2531409750","https://openalex.org/W2549139847","https://openalex.org/W2560023338","https://openalex.org/W2565639579","https://openalex.org/W2601564443","https://openalex.org/W2752782242","https://openalex.org/W2765407302","https://openalex.org/W2787091153","https://openalex.org/W2806070179","https://openalex.org/W2884822772","https://openalex.org/W2896457183","https://openalex.org/W2922509574","https://openalex.org/W2928165649","https://openalex.org/W2949718784","https://openalex.org/W2955425717","https://openalex.org/W2963091558","https://openalex.org/W2963150697","https://openalex.org/W2963263347","https://openalex.org/W2963341956","https://openalex.org/W2963403868","https://openalex.org/W2963420686","https://openalex.org/W2963446712","https://openalex.org/W2963727650","https://openalex.org/W2963855133","https://openalex.org/W2964241181","https://openalex.org/W2964309882","https://openalex.org/W2981413347","https://openalex.org/W2982220924","https://openalex.org/W2983446232","https://openalex.org/W2985459778","https://openalex.org/W3014030224","https://openalex.org/W3014641072","https://openalex.org/W3016719260","https://openalex.org/W3034445277","https://openalex.org/W3034885317","https://openalex.org/W3035284526","https://openalex.org/W3035421056","https://openalex.org/W3035682985","https://openalex.org/W3088934216","https://openalex.org/W3094502228","https://openalex.org/W3096609285","https://openalex.org/W3107634219","https://openalex.org/W3125364632","https://openalex.org/W3129603602","https://openalex.org/W3133696297","https://openalex.org/W3137278571","https://openalex.org/W3138516171","https://openalex.org/W3138994021","https://openalex.org/W3146097248","https://openalex.org/W3157528469","https://openalex.org/W3170227631","https://openalex.org/W3170874841","https://openalex.org/W3171206729","https://openalex.org/W3172509117","https://openalex.org/W3175095612","https://openalex.org/W3186033197","https://openalex.org/W3204563069","https://openalex.org/W3211432419","https://openalex.org/W4214634256","https://openalex.org/W4214709605","https://openalex.org/W4246193833","https://openalex.org/W4297665946","https://openalex.org/W4298395628","https://openalex.org/W4385245566","https://openalex.org/W6600213771","https://openalex.org/W6618372016","https://openalex.org/W6637373629","https://openalex.org/W6674330103","https://openalex.org/W6684191040","https://openalex.org/W6726497184","https://openalex.org/W6739901393","https://openalex.org/W6745136726","https://openalex.org/W6762718338","https://openalex.org/W6763367864","https://openalex.org/W6779879114","https://openalex.org/W6784333009","https://openalex.org/W6788135285","https://openalex.org/W6788467338","https://openalex.org/W6790690058","https://openalex.org/W6791793911","https://openalex.org/W6791978202","https://openalex.org/W6794345597","https://openalex.org/W6803916128"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4313906399","https://openalex.org/W4321487865","https://openalex.org/W4321444604","https://openalex.org/W2811106690","https://openalex.org/W2936819511","https://openalex.org/W4239306820","https://openalex.org/W2947043951","https://openalex.org/W2318112981","https://openalex.org/W4312417841"],"abstract_inverted_index":{"Transformer":[0,80,211],"with":[1,22,139],"self-attention":[2,37],"has":[3],"led":[4],"to":[5,43,97,126,142,163],"the":[6,16,45,62,91,99,108,136,144,165,174,191,235],"revolutionizing":[7],"of":[8,18,32,51,101,110,131,169,173,221,237],"natural":[9],"language":[10],"processing":[11],"field,":[12],"and":[13,54,105,176,230],"recently":[14],"inspires":[15],"emergence":[17],"Transformer-style":[19,76,206],"architecture":[20],"design":[21,73,87],"competitive":[23],"results":[24],"in":[25,190,201],"numerous":[26],"computer":[27],"vision":[28],"tasks.":[29],"Nevertheless,":[30],"most":[31],"existing":[33],"designs":[34],"directly":[35],"employ":[36],"over":[38,217],"a":[39,74,122,127,205,218,240],"2D":[40],"feature":[41],"map":[42],"obtain":[44],"attention":[46,103,147,156],"matrix":[47,104,148,157],"based":[48],"on":[49,90],"pairs":[50],"isolated":[52],"queries":[53,141],"keys":[55,67,96,120,138],"at":[56,247],"each":[57,198],"spatial":[58],"location,":[59],"but":[60],"leave":[61],"rich":[63],"contexts":[64],"among":[65,94],"neighbor":[66],"under-exploited.":[68],"In":[69],"this":[70],"work,":[71],"we":[72,233],"novel":[75],"module,":[77],"i.e.,":[78],"Contextual":[79,210],"(CoT)":[81],"block,":[82],"for":[83],"visual":[84,111],"recognition.":[85],"Such":[86],"fully":[88],"capitalizes":[89],"contextual":[92,129,167,178],"information":[93],"input":[95,119,140,161],"guide":[98],"learning":[100],"dynamic":[102,145,166,177],"thus":[106],"strengthens":[107],"capacity":[109],"representation.":[112],"Technically,":[113],"CoT":[114,186],"block":[115,187],"first":[116],"contextually":[117],"encodes":[118],"via":[121],"3\u00d73":[123,199],"convolution,":[124],"leading":[125],"static":[128,175],"representation":[130,168],"inputs.":[132,170],"We":[133],"further":[134],"concatenate":[135],"encoded":[137],"learn":[143],"multi-head":[146],"through":[149],"two":[150],"consecutive":[151],"1\u00d71":[152],"convolutions.":[153],"The":[154,171],"learnt":[155],"is":[158,188,245],"multiplied":[159],"by":[160],"values":[162],"achieve":[164],"fusion":[172],"representations":[179],"are":[180],"finally":[181],"taken":[182],"as":[183,209,239],"outputs.":[184],"Our":[185],"appealing":[189],"view":[192],"that":[193],"it":[194],"can":[195],"readily":[196],"replace":[197],"convolution":[200],"ResNet":[202],"architectures,":[203],"yielding":[204],"backbone":[207],"named":[208],"Networks":[212],"(CoTNet).":[213],"Through":[214],"extensive":[215],"experiments":[216],"wide":[219],"range":[220],"applications":[222],"(e.g.,":[223],"image":[224],"recognition,":[225],"object":[226],"detection,":[227],"instance":[228],"segmentation,":[229],"semantic":[231],"segmentation),":[232],"validate":[234],"superiority":[236],"CoTNet":[238],"stronger":[241],"backbone.":[242],"Source":[243],"code":[244],"available":[246],"https://github.com/JDAI-CV/CoTNet.":[248]},"counts_by_year":[{"year":2026,"cited_by_count":46},{"year":2025,"cited_by_count":187},{"year":2024,"cited_by_count":223},{"year":2023,"cited_by_count":171},{"year":2022,"cited_by_count":65},{"year":2021,"cited_by_count":3}],"updated_date":"2026-06-02T09:04:35.204637","created_date":"2025-10-10T00:00:00"}