{"id":"https://openalex.org/W4320009770","doi":"https://doi.org/10.1109/tpami.2023.3243048","title":"Conformer: Local Features Coupling Global Representations for Recognition and Detection","display_name":"Conformer: Local Features Coupling Global Representations for Recognition and Detection","publication_year":2023,"publication_date":"2023-02-07","ids":{"openalex":"https://openalex.org/W4320009770","doi":"https://doi.org/10.1109/tpami.2023.3243048","pmid":"https://pubmed.ncbi.nlm.nih.gov/37022836"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2023.3243048","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3243048","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/A5038511307","display_name":"Zhiliang Peng","orcid":"https://orcid.org/0000-0002-6643-9329"},"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":"Zhiliang Peng","raw_affiliation_strings":["School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences (UCAS), Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences (UCAS), Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011636193","display_name":"Zonghao Guo","orcid":"https://orcid.org/0000-0001-8492-2130"},"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":false,"raw_author_name":"Zonghao Guo","raw_affiliation_strings":["School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences (UCAS), Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences (UCAS), Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101651673","display_name":"Wei Huang","orcid":"https://orcid.org/0000-0001-8899-0069"},"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":false,"raw_author_name":"Wei Huang","raw_affiliation_strings":["School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences (UCAS), Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences (UCAS), Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100631216","display_name":"Yaowei Wang","orcid":"https://orcid.org/0000-0003-2197-9038"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaowei Wang","raw_affiliation_strings":["Peng Cheng Laboratory, Shenzhen, Guangdong Province, China"],"affiliations":[{"raw_affiliation_string":"Peng Cheng Laboratory, Shenzhen, Guangdong Province, China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075290241","display_name":"Lingxi Xie","orcid":"https://orcid.org/0000-0003-4831-9451"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingxi Xie","raw_affiliation_strings":["Huawei Cloud, Shenzhen, Guangdong Province, China"],"affiliations":[{"raw_affiliation_string":"Huawei Cloud, Shenzhen, Guangdong Province, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110088325","display_name":"Jianbin Jiao","orcid":"https://orcid.org/0000-0003-0454-3929"},"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":false,"raw_author_name":"Jianbin Jiao","raw_affiliation_strings":["School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences (UCAS), Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences (UCAS), Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100393506","display_name":"Qi Tian","orcid":"https://orcid.org/0000-0002-7252-5047"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Tian","raw_affiliation_strings":["Huawei Cloud, Shenzhen, Guangdong Province, China"],"affiliations":[{"raw_affiliation_string":"Huawei Cloud, Shenzhen, Guangdong Province, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015317495","display_name":"Qixiang Ye","orcid":null},"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":false,"raw_author_name":"Qixiang Ye","raw_affiliation_strings":["School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences (UCAS), Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences (UCAS), Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5038511307"],"corresponding_institution_ids":["https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":19.2903,"has_fulltext":false,"cited_by_count":160,"citation_normalized_percentile":{"value":0.99626012,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"45","issue":"8","first_page":"9454","last_page":"9468"},"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":0.9993000030517578,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9965999722480774,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.752626895904541},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7080802917480469},{"id":"https://openalex.org/keywords/conformational-isomerism","display_name":"Conformational isomerism","score":0.662775993347168},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5988724231719971},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5839996337890625},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.575239896774292},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5291198492050171},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.49685052037239075},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.464047372341156},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.46402934193611145},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.46271181106567383},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3187733590602875},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06824618577957153}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.752626895904541},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7080802917480469},{"id":"https://openalex.org/C18705241","wikidata":"https://www.wikidata.org/wiki/Q1128023","display_name":"Conformational isomerism","level":3,"score":0.662775993347168},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5988724231719971},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5839996337890625},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.575239896774292},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5291198492050171},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.49685052037239075},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.464047372341156},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.46402934193611145},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.46271181106567383},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3187733590602875},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06824618577957153},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C32909587","wikidata":"https://www.wikidata.org/wiki/Q11369","display_name":"Molecule","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007858","descriptor_name":"Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007858","descriptor_name":"Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007858","descriptor_name":"Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2023.3243048","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3243048","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:37022836","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37022836","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":[{"id":"https://metadata.un.org/sdg/17","score":0.4099999964237213,"display_name":"Partnerships for the goals"}],"awards":[{"id":"https://openalex.org/G1295000622","display_name":null,"funder_award_id":"61836012","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6113573069","display_name":null,"funder_award_id":"62171431","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6735075065","display_name":null,"funder_award_id":"62225208","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":125,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1686810756","https://openalex.org/W1836465849","https://openalex.org/W1861492603","https://openalex.org/W2014788144","https://openalex.org/W2049694710","https://openalex.org/W2097117768","https://openalex.org/W2108598243","https://openalex.org/W2131344117","https://openalex.org/W2151103935","https://openalex.org/W2163352848","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2295107390","https://openalex.org/W2549139847","https://openalex.org/W2565639579","https://openalex.org/W2601564443","https://openalex.org/W2752782242","https://openalex.org/W2884585870","https://openalex.org/W2896457183","https://openalex.org/W2898732869","https://openalex.org/W2908510526","https://openalex.org/W2947707615","https://openalex.org/W2953937638","https://openalex.org/W2955425717","https://openalex.org/W2962766617","https://openalex.org/W2962850830","https://openalex.org/W2963091558","https://openalex.org/W2963150697","https://openalex.org/W2963351448","https://openalex.org/W2963446712","https://openalex.org/W2963840672","https://openalex.org/W2964080601","https://openalex.org/W2964241181","https://openalex.org/W2964350391","https://openalex.org/W2981413347","https://openalex.org/W2982220924","https://openalex.org/W3014641072","https://openalex.org/W3033210410","https://openalex.org/W3034429256","https://openalex.org/W3034445277","https://openalex.org/W3034747217","https://openalex.org/W3035396860","https://openalex.org/W3035422918","https://openalex.org/W3037492894","https://openalex.org/W3096609285","https://openalex.org/W3097055324","https://openalex.org/W3107331169","https://openalex.org/W3108849448","https://openalex.org/W3114896399","https://openalex.org/W3121523901","https://openalex.org/W3122239467","https://openalex.org/W3129012257","https://openalex.org/W3131500599","https://openalex.org/W3132890542","https://openalex.org/W3136416617","https://openalex.org/W3137278571","https://openalex.org/W3138516171","https://openalex.org/W3139049060","https://openalex.org/W3142837074","https://openalex.org/W3145444543","https://openalex.org/W3160694286","https://openalex.org/W3170778815","https://openalex.org/W3170841864","https://openalex.org/W3170874841","https://openalex.org/W3171087525","https://openalex.org/W3171125843","https://openalex.org/W3171206729","https://openalex.org/W3171660447","https://openalex.org/W3172509117","https://openalex.org/W3172752666","https://openalex.org/W3175544090","https://openalex.org/W3177096435","https://openalex.org/W3180134609","https://openalex.org/W3199093552","https://openalex.org/W3203974803","https://openalex.org/W3206263120","https://openalex.org/W4214493665","https://openalex.org/W4214588794","https://openalex.org/W4214614183","https://openalex.org/W4214627427","https://openalex.org/W4214713996","https://openalex.org/W4286914341","https://openalex.org/W4292779060","https://openalex.org/W4312443924","https://openalex.org/W4312453657","https://openalex.org/W4385245566","https://openalex.org/W6620707391","https://openalex.org/W6637373629","https://openalex.org/W6638667902","https://openalex.org/W6639102338","https://openalex.org/W6678174250","https://openalex.org/W6684191040","https://openalex.org/W6696085341","https://openalex.org/W6730903564","https://openalex.org/W6739901393","https://openalex.org/W6755207826","https://openalex.org/W6757817989","https://openalex.org/W6760424586","https://openalex.org/W6762718338","https://openalex.org/W6763468762","https://openalex.org/W6764990469","https://openalex.org/W6778485988","https://openalex.org/W6778883912","https://openalex.org/W6779248606","https://openalex.org/W6779430525","https://openalex.org/W6779879114","https://openalex.org/W6780226713","https://openalex.org/W6784094891","https://openalex.org/W6784923365","https://openalex.org/W6786423403","https://openalex.org/W6786585107","https://openalex.org/W6787826751","https://openalex.org/W6788135285","https://openalex.org/W6788620109","https://openalex.org/W6790236297","https://openalex.org/W6790703111","https://openalex.org/W6792695861","https://openalex.org/W6793164127","https://openalex.org/W6796814978","https://openalex.org/W6796931752","https://openalex.org/W6797790494","https://openalex.org/W6801230688","https://openalex.org/W6801655670","https://openalex.org/W6802599522"],"related_works":["https://openalex.org/W2023036309","https://openalex.org/W1972863456","https://openalex.org/W2089371831","https://openalex.org/W2052399476","https://openalex.org/W2810163160","https://openalex.org/W3083970380","https://openalex.org/W2037964119","https://openalex.org/W4220905048","https://openalex.org/W4385077663","https://openalex.org/W4309346246"],"abstract_inverted_index":{"With":[0,20],"convolution":[1,53],"operations,":[2],"Convolutional":[3],"Neural":[4],"Networks":[5],"(CNNs)":[6],"are":[7,94],"good":[8],"at":[9],"extracting":[10],"local":[11,34,69,89],"features":[12,70],"but":[13,31],"experience":[14],"difficulty":[15],"to":[16,48,96,109,144],"capture":[17,27],"global":[18,73,92],"representations.":[19],"cascaded":[21],"self-attention":[22,56],"modules,":[23],"vision":[24],"transformers":[25],"can":[26],"long-distance":[28],"feature":[29,35,65,118],"dependencies":[30,93],"unfortunately":[32],"deteriorate":[33],"details.":[36],"In":[37],"this":[38],"paper,":[39],"we":[40],"propose":[41,102],"a":[42,84,103,146],"hybrid":[43],"network":[44],"structure,":[45],"termed":[46],"Conformer,":[47],"take":[49],"both":[50],"advantages":[51],"of":[52,67],"operations":[54],"and":[55,71,91,111,128,138],"mechanisms":[57],"for":[58,135],"enhanced":[59],"representation":[60],"learning.":[61],"Conformer":[62,82],"roots":[63],"in":[64,78,120],"coupling":[66,119],"CNN":[68],"transformer":[72],"representations":[74],"under":[75],"different":[76],"resolutions":[77],"an":[79,121],"interactive":[80],"fashion.":[81,124],"adopts":[83],"dual":[85],"structure":[86],"so":[87],"that":[88],"details":[90],"retained":[95],"the":[97],"maximum":[98],"extent.":[99],"We":[100],"also":[101],"Conformer-based":[104],"detector":[105],"(ConformerDet),":[106],"which":[107],"learns":[108],"predict":[110],"refine":[112],"object":[113,139],"proposals,":[114],"by":[115],"performing":[116],"region-level":[117],"augmented":[122],"cross-attention":[123],"Experiments":[125],"on":[126],"ImageNet":[127],"MS":[129],"COCO":[130],"datasets":[131],"validate":[132],"Conformer's":[133],"superiority":[134],"visual":[136],"recognition":[137],"detection,":[140],"demonstrating":[141],"its":[142],"potential":[143],"be":[145],"general":[147],"backbone":[148],"network.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":16},{"year":2025,"cited_by_count":79},{"year":2024,"cited_by_count":50},{"year":2023,"cited_by_count":15}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}
