{"id":"https://openalex.org/W4387968053","doi":"https://doi.org/10.1145/3581783.3612153","title":"Exploring Motion Cues for Video Test-Time Adaptation","display_name":"Exploring Motion Cues for Video Test-Time Adaptation","publication_year":2023,"publication_date":"2023-10-26","ids":{"openalex":"https://openalex.org/W4387968053","doi":"https://doi.org/10.1145/3581783.3612153"},"language":"en","primary_location":{"id":"doi:10.1145/3581783.3612153","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3612153","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","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/A5018498977","display_name":"Runhao Zeng","orcid":"https://orcid.org/0000-0001-8694-4245"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Runhao Zeng","raw_affiliation_strings":["Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101447665","display_name":"Qi Deng","orcid":"https://orcid.org/0009-0004-7475-0127"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Deng","raw_affiliation_strings":["South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103209793","display_name":"Huixuan Xu","orcid":"https://orcid.org/0009-0001-1224-3080"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huixuan Xu","raw_affiliation_strings":["South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064880801","display_name":"Shuaicheng Niu","orcid":"https://orcid.org/0000-0001-8212-1831"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Shuaicheng Niu","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100326501","display_name":"Jian Chen","orcid":"https://orcid.org/0000-0003-4769-1526"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Chen","raw_affiliation_strings":["South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5018498977"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":0.3576,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.60517284,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1840","last_page":"1850"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9990000128746033,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9990000128746033,"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":0.9962999820709229,"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":0.9911999702453613,"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":0.8121583461761475},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6934539079666138},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6356344223022461},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6261433362960815},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5684614181518555},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5435753464698792},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5036749243736267},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4837327301502228},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4570183753967285},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41582009196281433},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38718608021736145}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8121583461761475},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6934539079666138},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6356344223022461},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6261433362960815},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5684614181518555},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5435753464698792},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5036749243736267},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4837327301502228},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4570183753967285},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41582009196281433},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38718608021736145},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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:10.1145/3581783.3612153","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3612153","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.6700000166893005}],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1477544716","display_name":null,"funder_award_id":"Guangdong","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2981938667","display_name":null,"funder_award_id":"Shenzhen","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4015785278","display_name":null,"funder_award_id":"2019B1515130001","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"},{"id":"https://openalex.org/G4860469773","display_name":null,"funder_award_id":"62202311","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5182208057","display_name":null,"funder_award_id":"30001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5939423041","display_name":null,"funder_award_id":"Technology","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G657063301","display_name":null,"funder_award_id":"2023A1515011512","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"},{"id":"https://openalex.org/G7033253288","display_name":null,"funder_award_id":"Grants","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7198236715","display_name":null,"funder_award_id":"20220809180405001","funder_id":"https://openalex.org/F4320316880","funder_display_name":"Natural Science Foundation of Shenzhen City"},{"id":"https://openalex.org/G7406505370","display_name":null,"funder_award_id":"62072186","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7608752429","display_name":null,"funder_award_id":"Talent","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7626431573","display_name":null,"funder_award_id":"51501151","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320316880","display_name":"Natural Science Foundation of Shenzhen City","ror":null},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320337998","display_name":"HORIZON EUROPE Excellent Science","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2625366777","https://openalex.org/W2798592524","https://openalex.org/W2884797191","https://openalex.org/W2962858109","https://openalex.org/W2981385151","https://openalex.org/W2981952612","https://openalex.org/W2990503944","https://openalex.org/W2992308087","https://openalex.org/W2997487053","https://openalex.org/W3040572086","https://openalex.org/W3093099460","https://openalex.org/W3126330900","https://openalex.org/W3181598125","https://openalex.org/W3206798603","https://openalex.org/W3214432945","https://openalex.org/W3214575451","https://openalex.org/W3215113235","https://openalex.org/W4212977191","https://openalex.org/W4214727094","https://openalex.org/W4296151224","https://openalex.org/W4312365002","https://openalex.org/W4312723578","https://openalex.org/W4313025443","https://openalex.org/W4386075698","https://openalex.org/W4386083076","https://openalex.org/W6600838504","https://openalex.org/W6745136726","https://openalex.org/W6842760672"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2125652721","https://openalex.org/W1540371141","https://openalex.org/W1549363203","https://openalex.org/W2116862786"],"abstract_inverted_index":{"Test-time":[0],"adaptation":[1,163,186],"(TTA)":[2],"aims":[3],"at":[4],"boosting":[5],"the":[6,55,62,119,145,174,185],"generalization":[7],"capability":[8],"of":[9,58],"a":[10,77,104,126,134,155,167],"trained":[11],"model":[12,146],"by":[13,165,190],"conducting":[14],"self-/un-supervised":[15],"learning":[16,80,130],"during":[17],"testing":[18],"in":[19,73,178],"real-world":[20],"applications.":[21],"Though":[22],"TTA":[23,31,40,180],"on":[24,193,204,214],"image-based":[25,39],"tasks":[26,44],"has":[27],"seen":[28],"significant":[29],"progress,":[30],"techniques":[32],"for":[33,82,138],"video":[34,43,59,83,150,206],"remain":[35],"scarce.":[36],"Naively":[37],"introducing":[38],"methods":[41,51],"into":[42],"may":[45],"achieve":[46],"limited":[47],"performance,":[48],"since":[49],"these":[50],"do":[52],"not":[53],"consider":[54],"special":[56],"nature":[57],"tasks,":[60],"e.g.,":[61],"motion":[63,71,91,112,120],"information.":[64],"In":[65],"this":[66],"paper,":[67],"we":[68,124,153],"propose":[69,103,125],"leveraging":[70],"cues":[72],"videos":[74],"to":[75,109,132,147,160,173],"design":[76],"new":[78],"test-time":[79],"scheme":[81,108,159],"classification.":[84],"We":[85],"extract":[86,148],"spatial":[87],"appearance":[88,115],"and":[89,100,102,113,140],"dynamic":[90],"clip":[92],"features":[93],"using":[94],"two":[95,215],"sampling":[96,158],"rates":[97],"(i.e.,":[98],"slow":[99,114],"fast)":[101],"fast-to-slow":[105],"unidirectional":[106],"alignment":[107],"align":[110],"fast":[111],"features,":[116],"thereby":[117],"enhancing":[118],"encoding":[121],"ability.":[122],"Additionally,":[123],"slow-fast":[127],"dual":[128],"contrastive":[129],"strategy":[131],"learn":[133],"joint":[135],"feature":[136],"space":[137],"fastly":[139],"slowly":[141],"sampled":[142],"clips,":[143],"guiding":[144],"discriminative":[149],"features.":[151],"Lastly,":[152],"introduce":[154],"stochastic":[156],"pseudo-negative":[157,170],"provide":[161],"better":[162],"supervision":[164],"selecting":[166],"more":[168],"reliable":[169],"label":[171,176],"compared":[172],"pseudo-positive":[175],"used":[177],"prior":[179],"methods.":[181],"This":[182],"technique":[183],"reduces":[184],"difficulty":[187],"often":[188],"caused":[189],"poor":[191],"performance":[192,203],"out-of-distribution":[194],"test":[195],"data":[196],"before":[197],"adaptation.":[198],"Our":[199],"approach":[200],"significantly":[201],"improves":[202],"various":[205],"classification":[207],"backbones,":[208],"as":[209],"demonstrated":[210],"through":[211],"extensive":[212],"experiments":[213],"benchmark":[216],"datasets.":[217]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}
