{"id":"https://openalex.org/W4386071593","doi":"https://doi.org/10.1109/cvpr52729.2023.02314","title":"TIPI: Test Time Adaptation with Transformation Invariance","display_name":"TIPI: Test Time Adaptation with Transformation Invariance","publication_year":2023,"publication_date":"2023-06-01","ids":{"openalex":"https://openalex.org/W4386071593","doi":"https://doi.org/10.1109/cvpr52729.2023.02314"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr52729.2023.02314","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52729.2023.02314","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/A5081134111","display_name":"An-phi Nguyen","orcid":"https://orcid.org/0000-0003-4998-5931"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"A. Tuan Nguyen","raw_affiliation_strings":["University of Oxford"],"affiliations":[{"raw_affiliation_string":"University of Oxford","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086423509","display_name":"Thanh Nguyen-Tang","orcid":"https://orcid.org/0000-0002-1917-2190"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Thanh Nguyen-Tang","raw_affiliation_strings":["Johns Hopkins University"],"affiliations":[{"raw_affiliation_string":"Johns Hopkins University","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113969216","display_name":"Ser-Nam Lim","orcid":"https://orcid.org/0000-0001-9525-0288"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ser-Nam Lim","raw_affiliation_strings":["Meta AI"],"affiliations":[{"raw_affiliation_string":"Meta AI","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042899882","display_name":"Philip H. S. Torr","orcid":null},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Philip H.S. Torr","raw_affiliation_strings":["University of Oxford"],"affiliations":[{"raw_affiliation_string":"University of Oxford","institution_ids":["https://openalex.org/I40120149"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5081134111"],"corresponding_institution_ids":["https://openalex.org/I40120149"],"apc_list":null,"apc_paid":null,"fwci":3.5811,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.94270519,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"24162","last_page":"24171"},"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":0.9998999834060669,"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":0.9998999834060669,"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":0.9995999932289124,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9961000084877014,"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":0.7481608390808105},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5773124694824219},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5432144403457642},{"id":"https://openalex.org/keywords/test-data","display_name":"Test data","score":0.5206124782562256},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.503886878490448},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5037431120872498},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.49708274006843567},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.48467257618904114},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4638664126396179},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.41494908928871155},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34834569692611694},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0975695252418518}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7481608390808105},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5773124694824219},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5432144403457642},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.5206124782562256},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.503886878490448},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5037431120872498},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.49708274006843567},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.48467257618904114},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4638664126396179},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.41494908928871155},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34834569692611694},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0975695252418518},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cvpr52729.2023.02314","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52729.2023.02314","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"},{"id":"pmh:oai:ora.ox.ac.uk:uuid:6f6a8249-4ae9-4064-9e3e-f8de8d5ac154","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306402636","display_name":"Oxford University Research Archive (ORA) (University of Oxford)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I40120149","host_organization_name":"University of Oxford","host_organization_lineage":["https://openalex.org/I40120149"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symplectic Elements","raw_type":"http://purl.org/coar/resource_type/c_5794"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.49000000953674316,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1617650991","https://openalex.org/W1731081199","https://openalex.org/W1945616565","https://openalex.org/W2100659887","https://openalex.org/W2104094955","https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2335728318","https://openalex.org/W2431080869","https://openalex.org/W2889965839","https://openalex.org/W2963043696","https://openalex.org/W2964137095","https://openalex.org/W2964159205","https://openalex.org/W3035743198","https://openalex.org/W3036825277","https://openalex.org/W3040572086","https://openalex.org/W3118608800","https://openalex.org/W3119543788","https://openalex.org/W3214432945","https://openalex.org/W3214575451","https://openalex.org/W4225774191","https://openalex.org/W4287119605","https://openalex.org/W4287330095","https://openalex.org/W4287637349","https://openalex.org/W4287646898","https://openalex.org/W4288020585","https://openalex.org/W4288404646","https://openalex.org/W4293846201","https://openalex.org/W4320858551","https://openalex.org/W6631190155","https://openalex.org/W6636267554","https://openalex.org/W6637618735","https://openalex.org/W6640425456","https://openalex.org/W6683124652","https://openalex.org/W6687400500","https://openalex.org/W6717772578","https://openalex.org/W6739868092","https://openalex.org/W6754038005","https://openalex.org/W6754855011","https://openalex.org/W6757555829","https://openalex.org/W6770578729","https://openalex.org/W6780128236","https://openalex.org/W6780178746","https://openalex.org/W6780666095","https://openalex.org/W6783600611","https://openalex.org/W6784493056","https://openalex.org/W6788125050","https://openalex.org/W6790146069","https://openalex.org/W6796051603","https://openalex.org/W6803247036","https://openalex.org/W6804111167","https://openalex.org/W6811147225","https://openalex.org/W6850116420"],"related_works":["https://openalex.org/W2997567050","https://openalex.org/W1483272040","https://openalex.org/W4283377908","https://openalex.org/W1526712007","https://openalex.org/W1533421371","https://openalex.org/W2003050223","https://openalex.org/W2091777911","https://openalex.org/W4394775207","https://openalex.org/W2028936140","https://openalex.org/W2043884319"],"abstract_inverted_index":{"When":[0],"deploying":[1],"a":[2,7,79,115,156],"machine":[3],"learning":[4],"model":[5,89],"to":[6,81,90,95,113,214],"new":[8,42,97],"environment,":[9],"we":[10,33,46,188,212],"often":[11,173,199],"encounter":[12],"the":[13,19,26,50,66,71,88,96,109,119,127,147,162,167,220,232],"distribution":[14,22,68],"shift":[15],"problem":[16],"-":[17],"meaning":[18],"target":[20,122,131,168],"data":[21,52,67,98,104],"is":[23,112,140,172,194,247,263,286],"different":[24],"from":[25],"model's":[27,72,148,233],"training":[28,149,160],"distribution.":[29],"In":[30,124],"this":[31,41,83,191,207,210],"paper,":[32,211],"assume":[34],"that":[35,45,61,190],"labels":[36],"are":[37],"not":[38,48,144,153,195],"provided":[39],"for":[40,54],"domain,":[43],"and":[44,142,259,276],"do":[47],"store":[49],"source":[51,163],"(e.g.,":[53,151,178],"privacy":[55],"reasons).":[56],"It":[57],"has":[58,134],"been":[59],"shown":[60],"even":[62],"small":[63,174,202,266,270],"shifts":[64],"in":[65,175,186,209,252,273,281],"can":[69],"affect":[70],"performance":[73,234],"severely.":[74],"Test":[75],"Time":[76],"Adaptation":[77],"offers":[78],"means":[80],"combat":[82],"problem,":[84,208],"as":[85,138,166,219,271],"it":[86,139,198],"allows":[87],"adapt":[91],"during":[92,159,223],"test":[93,103],"time":[94,242],"distribution,":[99],"using":[100],"only":[101],"unlabeled":[102,121],"batches.":[105],"To":[106,205],"achieve":[107],"this,":[108],"predominant":[110],"approach":[111],"optimize":[114],"surrogate":[116,192,221],"loss":[117,193,222],"on":[118,130,161],"test-time":[120,224],"data.":[123],"particular,":[125],"minimizing":[126],"prediction's":[128],"entropy":[129],"samples":[132],"[34]":[133,280],"received":[135],"much":[136],"interest":[137],"task-agnostic":[141],"does":[143,152],"require":[145,154],"altering":[146],"phase":[150],"adding":[155],"self-supervised":[157],"task":[158],"domain).":[164],"However,":[165],"data's":[169],"batch":[170,203,267],"size":[171],"real-world":[176],"scenarios":[177],"autonomous":[179],"driving":[180],"models":[181],"process":[182],"each":[183],"few":[184],"frames":[185],"real-time),":[187],"argue":[189],"optimal":[196],"since":[197],"collapses":[200],"with":[201,244,249],"sizes.":[204],"tackle":[206],"propose":[213],"use":[215],"an":[216],"invariance":[217],"regularizer":[218],"adaptation,":[225],"motivated":[226],"by":[227],"our":[228,274],"theoretical":[229],"results":[230],"regarding":[231],"under":[235],"input":[236],"transformations.":[237],"The":[238],"resulting":[239],"method":[240],"(TIPI-Test":[241],"adaPtation":[243],"transformation":[245],"Invariance)":[246],"validated":[248],"extensive":[250],"experiments":[251],"various":[253],"benchmarks":[254],"(Cifar10-C,":[255],"Cifar100-C,":[256],"ImageNet-C,":[257],"DIGITS,":[258],"VisDA17).":[260],"Remarkably,":[261],"TIPI":[262],"robust":[264],"against":[265],"sizes":[268],"(as":[269],"2":[272],"experiments),":[275],"consistently":[277],"outperforms":[278],"TENT":[279],"all":[282],"settings.":[283],"Our":[284],"code":[285],"released":[287],"at":[288],"https://github.com/atuannguyen/TIPI.":[289]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":13}],"updated_date":"2026-04-23T09:07:50.710637","created_date":"2025-10-10T00:00:00"}