{"id":"https://openalex.org/W7124454052","doi":"https://doi.org/10.1109/tmm.2026.3654466","title":"Ranking-Based Self-Supervised Representation Learning for Skeleton-Based Action Recognition","display_name":"Ranking-Based Self-Supervised Representation Learning for Skeleton-Based Action Recognition","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7124454052","doi":"https://doi.org/10.1109/tmm.2026.3654466"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2026.3654466","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2026.3654466","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Multimedia","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://nottingham-repository.worktribe.com/preview/59585320/TMM25.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008067346","display_name":"Bizhu Wu","orcid":"https://orcid.org/0000-0002-6783-6561"},"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":false,"raw_author_name":"Bizhu Wu","raw_affiliation_strings":["Computer Vision Institute, School of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-6783-6561","affiliations":[{"raw_affiliation_string":"Computer Vision Institute, School of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123249939","display_name":"Junliang Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Junliang Chen","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, The Hong Kong Polytechnic University, Hong Kong, SAR, China"],"raw_orcid":"https://orcid.org/0000-0001-7516-9546","affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, The Hong Kong Polytechnic University, Hong Kong, SAR, China","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044361651","display_name":"Jinheng Xie","orcid":"https://orcid.org/0000-0001-5678-4500"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Jinheng Xie","raw_affiliation_strings":["Department of Electrical and Computer Engineering, National University of Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0001-5678-4500","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5094146033","display_name":"Qiufu Li","orcid":null},"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":false,"raw_author_name":"Qiufu Li","raw_affiliation_strings":["School of Artificial Intelligence, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-8120-6531","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123169457","display_name":"Jianfeng Ren","orcid":null},"institutions":[{"id":"https://openalex.org/I13591777","display_name":"University of Nottingham Ningbo China","ror":"https://ror.org/03y4dt428","country_code":"CN","type":"education","lineage":["https://openalex.org/I13591777","https://openalex.org/I142263535"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianfeng Ren","raw_affiliation_strings":["School of Computer Science, University of Nottingham Ningbo China, Ningbo, China"],"raw_orcid":"https://orcid.org/0000-0003-4619-6590","affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Nottingham Ningbo China, Ningbo, China","institution_ids":["https://openalex.org/I13591777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046750599","display_name":"Ruibin Bai","orcid":"https://orcid.org/0000-0003-1722-568X"},"institutions":[{"id":"https://openalex.org/I13591777","display_name":"University of Nottingham Ningbo China","ror":"https://ror.org/03y4dt428","country_code":"CN","type":"education","lineage":["https://openalex.org/I13591777","https://openalex.org/I142263535"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruibin Bai","raw_affiliation_strings":["School of Computer Science, University of Nottingham Ningbo China, Ningbo, China"],"raw_orcid":"https://orcid.org/0000-0003-1722-568X","affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Nottingham Ningbo China, Ningbo, China","institution_ids":["https://openalex.org/I13591777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063920690","display_name":"Rong Qu","orcid":"https://orcid.org/0000-0001-8318-7509"},"institutions":[{"id":"https://openalex.org/I142263535","display_name":"University of Nottingham","ror":"https://ror.org/01ee9ar58","country_code":"GB","type":"education","lineage":["https://openalex.org/I142263535"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Rong Qu","raw_affiliation_strings":["School of Computer Science, University of Nottingham, Nottingham, U.K"],"raw_orcid":"https://orcid.org/0000-0001-8318-7509","affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Nottingham, Nottingham, U.K","institution_ids":["https://openalex.org/I142263535"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5123189230","display_name":"Linlin Shen","orcid":null},"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":false,"raw_author_name":"Linlin Shen","raw_affiliation_strings":["Computer Vision Institute, School of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-1420-0815","affiliations":[{"raw_affiliation_string":"Computer Vision Institute, School of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06450536,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"28","issue":null,"first_page":"4181","last_page":"4193"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9664999842643738,"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":0.9664999842643738,"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":0.004000000189989805,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.003000000026077032,"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/discriminative-model","display_name":"Discriminative model","score":0.7192999720573425},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.6783000230789185},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5849999785423279},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.5770999789237976},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5212000012397766},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5205000042915344},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.4862000048160553},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.48089998960494995},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.477400004863739}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.807200014591217},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7192999720573425},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.718999981880188},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.6783000230789185},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5849999785423279},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.5770999789237976},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5212000012397766},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5205000042915344},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4950999915599823},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.4862000048160553},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.48089998960494995},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.477400004863739},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.47530001401901245},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.43149998784065247},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3806000053882599},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.37070000171661377},{"id":"https://openalex.org/C18969341","wikidata":"https://www.wikidata.org/wiki/Q1169129","display_name":"Skeleton (computer programming)","level":2,"score":0.3537999987602234},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.35179999470710754},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.33660000562667847},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.29750001430511475},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.29600000381469727},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.2955999970436096},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.29179999232292175},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.26930001378059387},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.2540999948978424}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tmm.2026.3654466","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2026.3654466","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Multimedia","raw_type":"journal-article"},{"id":"pmh:oai:nottingham-repository.worktribe.com:59319794","is_oa":true,"landing_page_url":"https://nottingham-repository.worktribe.com/59319794/1/TMM25","pdf_url":"https://nottingham-repository.worktribe.com/preview/59585320/TMM25.pdf","source":{"id":"https://openalex.org/S4306402483","display_name":"Repository@Nottingham (University of Nottingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I142263535","host_organization_name":"University of Nottingham","host_organization_lineage":["https://openalex.org/I142263535"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Journal Article"}],"best_oa_location":{"id":"pmh:oai:nottingham-repository.worktribe.com:59319794","is_oa":true,"landing_page_url":"https://nottingham-repository.worktribe.com/59319794/1/TMM25","pdf_url":"https://nottingham-repository.worktribe.com/preview/59585320/TMM25.pdf","source":{"id":"https://openalex.org/S4306402483","display_name":"Repository@Nottingham (University of Nottingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I142263535","host_organization_name":"University of Nottingham","host_organization_lineage":["https://openalex.org/I142263535"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Journal Article"},"sustainable_development_goals":[{"score":0.7856894135475159,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G4600207245","display_name":null,"funder_award_id":"62576216","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":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7124454052.pdf","grobid_xml":"https://content.openalex.org/works/W7124454052.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recently,":[0],"researchers":[1],"have":[2],"achieved":[3],"significant":[4,197],"results":[5,136],"in":[6,26,45,103],"the":[7,14,19,27,84,89,138,155,170,175,190,207,217],"skeleton-based":[8],"action":[9],"recognition.":[10],"To":[11],"better":[12],"model":[13],"skeleton":[15,81,107],"sequences,":[16,108],"we":[17,66,77,109],"drive":[18],"encoder":[20],"to":[21,38,57,95,123,126],"learn":[22,58,128],"more":[23,51,59],"discriminative":[24,99],"representations":[25],"self-supervised":[28,70,163],"setting.":[29,192],"We":[30],"find":[31],"that":[32,101,173],"instead":[33],"of":[34,80,106,160,224],"clustering":[35],"feature":[36,61],"vectors":[37],"assign":[39],"pseudo":[40],"labels":[41],"for":[42],"samples":[43],"as":[44,179],"DeepCluster,":[46],"ranking":[47,85],"them":[48],"is":[49],"a":[50,68,196],"reasonable,":[52],"reliable,":[53],"and":[54,146,158,186,216],"efficient":[55],"way":[56],"effective":[60],"representations.":[62],"With":[63],"this":[64],"intuition,":[65],"propose":[67,111],"novel":[69],"learning":[71,164],"framework,":[72],"<bold":[73,112,117],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[74,113,115,118,121,203,212,221],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">DeepRank</b>.":[75],"Specifically,":[76],"rank":[78],"triplets":[79],"sequences":[82],"with":[83],"labels,":[86],"obtained":[87],"from":[88,131],"relative":[90],"distances":[91],"among":[92],"them.":[93],"Besides,":[94],"deeply":[96],"mine":[97],"complementary":[98,129],"information":[100],"exists":[102],"different":[104],"modalities":[105],"further":[110],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">M</b>ulti-<bold":[114],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">V</b>iew":[116],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">DeepRank</b>":[119],"(<bold":[120],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">MV-DeepRank</b>)":[122],"enable":[124],"encoders":[125],"comprehensively":[127],"features":[130],"multiple":[132],"modalities.":[133],"Extensive":[134],"experimental":[135],"on":[137,199],"NTU":[139,141],"RGB+D,":[140],"RGB+D":[142],"120,":[143],"PKU-MMD":[144,147],"I,":[145],"II":[148],"datasets":[149],"under":[150,189],"various":[151],"evaluation":[152],"settings":[153],"demonstrate":[154],"generality,":[156],"transferability,":[157],"superiority":[159],"our":[161,167],"proposed":[162],"frameworks.":[165],"Notably,":[166],"frameworks":[168],"surpass":[169],"previous":[171],"methods":[172],"employ":[174],"same":[176],"backbone":[177],"networks":[178],"ours":[180],"by":[181],"at":[182],"least":[183],"1.8%":[184],"(ST-GCN)":[185],"2.1%":[187],"(STTFormer)":[188],"finetuning":[191],"Additionally,":[193],"DeepRank":[194],"gains":[195],"advantage":[198],"computational":[200],"complexities,":[201],"<inline-formula":[202,211,220],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><tex-math":[204,213,222],"notation=\"LaTeX\">$O(1)$</tex-math></inline-formula>,":[205],"over":[206],"contrastive":[208],"learning-based":[209],"methods,":[210,219],"notation=\"LaTeX\">$O(\\rm{batch":[214],"size})$</tex-math></inline-formula>,":[215],"clustering-based":[218],"notation=\"LaTeX\">$O(\\rm{number":[223],"clusters})$</tex-math></inline-formula>.":[225]},"counts_by_year":[],"updated_date":"2026-06-06T06:22:57.294733","created_date":"2026-01-17T00:00:00"}
