{"id":"https://openalex.org/W4386075759","doi":"https://doi.org/10.1109/cvpr52729.2023.01528","title":"Robust Test-Time Adaptation in Dynamic Scenarios","display_name":"Robust Test-Time Adaptation in Dynamic Scenarios","publication_year":2023,"publication_date":"2023-06-01","ids":{"openalex":"https://openalex.org/W4386075759","doi":"https://doi.org/10.1109/cvpr52729.2023.01528"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr52729.2023.01528","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52729.2023.01528","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-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/A5036532990","display_name":"Longhui Yuan","orcid":"https://orcid.org/0000-0002-3237-8409"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Longhui Yuan","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009558549","display_name":"Binhui Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Binhui Xie","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100415892","display_name":"Shuang Li","orcid":"https://orcid.org/0000-0001-9142-5036"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuang Li","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5036532990"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":16.4673,"has_fulltext":false,"cited_by_count":99,"citation_normalized_percentile":{"value":0.99420918,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"15922","last_page":"15932"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9898999929428101,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9898999929428101,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9794999957084656,"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/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9707000255584717,"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/computer-science","display_name":"Computer science","score":0.8592168092727661},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.6802698969841003},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.6146413683891296},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.6010059714317322},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.5072762370109558},{"id":"https://openalex.org/keywords/test-data","display_name":"Test data","score":0.5013751983642578},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.49225321412086487},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4416276216506958},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.43702229857444763},{"id":"https://openalex.org/keywords/scenario-testing","display_name":"Scenario testing","score":0.43099260330200195},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4198029041290283},{"id":"https://openalex.org/keywords/test-case","display_name":"Test case","score":0.4178798794746399},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.28760993480682373},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24547430872917175},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.1580783724784851}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8592168092727661},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.6802698969841003},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.6146413683891296},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.6010059714317322},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.5072762370109558},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.5013751983642578},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.49225321412086487},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4416276216506958},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.43702229857444763},{"id":"https://openalex.org/C80519477","wikidata":"https://www.wikidata.org/wiki/Q3532236","display_name":"Scenario testing","level":3,"score":0.43099260330200195},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4198029041290283},{"id":"https://openalex.org/C128942645","wikidata":"https://www.wikidata.org/wiki/Q1568346","display_name":"Test case","level":3,"score":0.4178798794746399},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28760993480682373},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24547430872917175},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.1580783724784851},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr52729.2023.01528","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52729.2023.01528","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.49000000953674316}],"awards":[{"id":"https://openalex.org/G2670821623","display_name":null,"funder_award_id":"2021YFB3301503","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G4762857569","display_name":null,"funder_award_id":"61902028","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/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":114,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1617650991","https://openalex.org/W1731081199","https://openalex.org/W1836465849","https://openalex.org/W1943830695","https://openalex.org/W2126151240","https://openalex.org/W2141129816","https://openalex.org/W2155858138","https://openalex.org/W2162651021","https://openalex.org/W2165698076","https://openalex.org/W2194775991","https://openalex.org/W2214409633","https://openalex.org/W2293363371","https://openalex.org/W2473930607","https://openalex.org/W2517041761","https://openalex.org/W2549139847","https://openalex.org/W2560647685","https://openalex.org/W2593768305","https://openalex.org/W2618530766","https://openalex.org/W2786808285","https://openalex.org/W2798658180","https://openalex.org/W2884282566","https://openalex.org/W2889945482","https://openalex.org/W2895281799","https://openalex.org/W2919115771","https://openalex.org/W2962687275","https://openalex.org/W2963043696","https://openalex.org/W2963107255","https://openalex.org/W2963826694","https://openalex.org/W2964115968","https://openalex.org/W2964137095","https://openalex.org/W2964189064","https://openalex.org/W2981720610","https://openalex.org/W2982204955","https://openalex.org/W3030364939","https://openalex.org/W3034526587","https://openalex.org/W3035000591","https://openalex.org/W3035701489","https://openalex.org/W3035762155","https://openalex.org/W3036825277","https://openalex.org/W3109042658","https://openalex.org/W3117088788","https://openalex.org/W3118608800","https://openalex.org/W3119543788","https://openalex.org/W3120575095","https://openalex.org/W3128475431","https://openalex.org/W3133542152","https://openalex.org/W3135384301","https://openalex.org/W3142917731","https://openalex.org/W3175042385","https://openalex.org/W3177415989","https://openalex.org/W3206154535","https://openalex.org/W3206798603","https://openalex.org/W3209325215","https://openalex.org/W3214432945","https://openalex.org/W3214575451","https://openalex.org/W3216968833","https://openalex.org/W4212977191","https://openalex.org/W4214715922","https://openalex.org/W4225774191","https://openalex.org/W4283034476","https://openalex.org/W4287637349","https://openalex.org/W4288044830","https://openalex.org/W4288404646","https://openalex.org/W4289639938","https://openalex.org/W4295312788","https://openalex.org/W4295934507","https://openalex.org/W4295938620","https://openalex.org/W4296151208","https://openalex.org/W4296151224","https://openalex.org/W4298116016","https://openalex.org/W4312365002","https://openalex.org/W4312644018","https://openalex.org/W4312717513","https://openalex.org/W4312897837","https://openalex.org/W4313025443","https://openalex.org/W4313184971","https://openalex.org/W4317038436","https://openalex.org/W4320858551","https://openalex.org/W6631190155","https://openalex.org/W6636267554","https://openalex.org/W6637618735","https://openalex.org/W6638667902","https://openalex.org/W6678977525","https://openalex.org/W6681588610","https://openalex.org/W6683124652","https://openalex.org/W6687400500","https://openalex.org/W6713132643","https://openalex.org/W6730251247","https://openalex.org/W6755287564","https://openalex.org/W6757555829","https://openalex.org/W6764645560","https://openalex.org/W6766978945","https://openalex.org/W6773490324","https://openalex.org/W6773992155","https://openalex.org/W6779928312","https://openalex.org/W6780128236","https://openalex.org/W6780178746","https://openalex.org/W6781506369","https://openalex.org/W6784493056","https://openalex.org/W6788125050","https://openalex.org/W6789380839","https://openalex.org/W6791861950","https://openalex.org/W6791875987","https://openalex.org/W6803227292","https://openalex.org/W6803247036","https://openalex.org/W6804111167","https://openalex.org/W6811147225","https://openalex.org/W6839200446","https://openalex.org/W6840679589","https://openalex.org/W6841163610","https://openalex.org/W6842574522","https://openalex.org/W6842760672","https://openalex.org/W6850116420"],"related_works":["https://openalex.org/W4389449520","https://openalex.org/W127192698","https://openalex.org/W2570600173","https://openalex.org/W2893008024","https://openalex.org/W2743735673","https://openalex.org/W4361801939","https://openalex.org/W2360131081","https://openalex.org/W2985941356","https://openalex.org/W2802243998","https://openalex.org/W1521014365"],"abstract_inverted_index":{"Test-time":[0],"adaptation":[1,91,165],"(TTA)":[2],"intends":[3],"to":[4,9,81,120,131,142,176],"adapt":[5],"the":[6,20,58,63,83,86,105,122,144,167],"pretrained":[7],"model":[8,84],"test":[10,15,30,64,78],"distributions":[11],"with":[12,135,153],"only":[13],"unlabeled":[14],"data":[16,31,37,65,79,107,134,170],"streams.":[17,171],"Most":[18],"of":[19,51,137],"previous":[21],"TTA":[22],"methods":[23],"have":[24],"achieved":[25],"great":[26],"success":[27],"on":[28,85,166],"simple":[29],"streams":[32,80],"such":[33,76],"as":[34],"independently":[35],"sampled":[36,67,169],"from":[38],"single":[39],"or":[40],"multiple":[41],"distributions.":[42],"However,":[43],"these":[44],"attempts":[45],"may":[46],"fail":[47],"in":[48,109],"dynamic":[49],"scenarios":[50],"real-world":[52],"applications":[53],"like":[54],"autonomous":[55],"driving,":[56],"where":[57],"environments":[59],"gradually":[60],"change":[61],"and":[62,139],"is":[66,129,174,188],"correlatively":[68,168],"over":[69],"time.":[70],"In":[71],"this":[72],"work,":[73],"we":[74,96,113,147],"explore":[75],"practical":[77,89],"deploy":[82],"fly,":[87],"namely":[88],"test-time":[90,164],"(PTTA).":[92],"To":[93],"do":[94],"so,":[95],"elaborate":[97],"a":[98,115,126,149,154,180],"Robust":[99],"Test-Time":[100],"Adaptation":[101],"(RoTTA)":[102],"method":[103,173],"against":[104],"complex":[106],"stream":[108],"PTTA.":[110],"More":[111],"specifically,":[112],"present":[114],"robust":[116],"batch":[117],"normalization":[118,123],"scheme":[119],"estimate":[121],"statistics.":[124],"Meanwhile,":[125],"memory":[127],"bank":[128],"utilized":[130],"sample":[132],"category-balanced":[133],"consideration":[136],"timeliness":[138],"uncertainty.":[140],"Further,":[141],"stabilize":[143],"training":[145],"procedure,":[146],"develop":[148],"time-aware":[150],"reweighting":[151],"strategy":[152],"teacher-student":[155],"model.":[156],"Extensive":[157],"experiments":[158],"prove":[159],"that":[160],"RoTTA":[161],"enables":[162],"continual":[163],"Our":[172],"easy":[175],"implement,":[177],"making":[178],"it":[179],"good":[181],"choice":[182],"for":[183],"rapid":[184],"deployment.":[185],"The":[186],"code":[187],"publicly":[189],"available":[190],"at":[191],"https://github.com/BIT-DA/RoTTA":[192]},"counts_by_year":[{"year":2026,"cited_by_count":15},{"year":2025,"cited_by_count":44},{"year":2024,"cited_by_count":40}],"updated_date":"2026-05-20T08:49:12.498775","created_date":"2025-10-10T00:00:00"}