{"id":"https://openalex.org/W7167254808","doi":"https://doi.org/10.1016/j.cosrev.2026.101030","title":"Beyond benchmark accuracy: A generalization-centered analysis of deep learning for skeleton-based human activity recognition","display_name":"Beyond benchmark accuracy: A generalization-centered analysis of deep learning for skeleton-based human activity recognition","publication_year":2026,"publication_date":"2026-07-03","ids":{"openalex":"https://openalex.org/W7167254808","doi":"https://doi.org/10.1016/j.cosrev.2026.101030"},"language":"en","primary_location":{"id":"doi:10.1016/j.cosrev.2026.101030","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.cosrev.2026.101030","pdf_url":null,"source":{"id":"https://openalex.org/S73121659","display_name":"Computer Science Review","issn_l":"1574-0137","issn":["1574-0137","1876-7745"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computer Science Review","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.cosrev.2026.101030","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100646564","display_name":"Yi Xia","orcid":"https://orcid.org/0000-0002-3846-0948"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yi Xia","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-3846-0948","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082853606","display_name":"Sira Yongchareon","orcid":"https://orcid.org/0000-0002-2880-6618"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sira Yongchareon","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-2880-6618","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050424888","display_name":"Raymond Lutui","orcid":"https://orcid.org/0009-0009-3908-6466"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Raymond Lutui","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0009-0009-3908-6466","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5080744092","display_name":"Quan Z. Sheng","orcid":"https://orcid.org/0000-0002-3326-4147"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Quan Z. Sheng","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-3326-4147","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":3300,"currency":"USD","value_usd":3300},"apc_paid":{"value":3300,"currency":"USD","value_usd":3300},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.83298755,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"62","issue":null,"first_page":"101030","last_page":"101030"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.7127000093460083,"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":0.7127000093460083,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.17579999566078186,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.019300000742077827,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.8162000179290771},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7732999920845032},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.6908000111579895},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.29820001125335693}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8356999754905701},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.8162000179290771},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7732999920845032},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.728600025177002},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.6908000111579895},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45179998874664307},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3246000111103058},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.29820001125335693},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.250900000333786},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.2506999969482422}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1016/j.cosrev.2026.101030","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.cosrev.2026.101030","pdf_url":null,"source":{"id":"https://openalex.org/S73121659","display_name":"Computer Science Review","issn_l":"1574-0137","issn":["1574-0137","1876-7745"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computer Science Review","raw_type":"journal-article"},{"id":"pmh:oai:openrepository.aut.ac.nz:10292/21560","is_oa":true,"landing_page_url":"http://hdl.handle.net/10292/21560","pdf_url":null,"source":{"id":"https://openalex.org/S4306401809","display_name":"Tuwhera (Auckland University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I39854758","host_organization_name":"Auckland University of Technology","host_organization_lineage":["https://openalex.org/I39854758"],"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":"doi:10.1016/j.cosrev.2026.101030","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.cosrev.2026.101030","pdf_url":null,"source":{"id":"https://openalex.org/S73121659","display_name":"Computer Science Review","issn_l":"1574-0137","issn":["1574-0137","1876-7745"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computer Science Review","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W2101032778","https://openalex.org/W2143004591","https://openalex.org/W2146055337","https://openalex.org/W2554408731","https://openalex.org/W2743357133","https://openalex.org/W2810685774","https://openalex.org/W2944006115","https://openalex.org/W2954146807","https://openalex.org/W2971710819","https://openalex.org/W2996249958","https://openalex.org/W3097033071","https://openalex.org/W4220663024","https://openalex.org/W4221152513","https://openalex.org/W4240042586","https://openalex.org/W4296478337","https://openalex.org/W4311752814","https://openalex.org/W4312661503","https://openalex.org/W4312825267","https://openalex.org/W4318200309","https://openalex.org/W4319027841","https://openalex.org/W4361247902","https://openalex.org/W4376274034","https://openalex.org/W4382314630","https://openalex.org/W4385834325","https://openalex.org/W4386090212","https://openalex.org/W4390738727","https://openalex.org/W4390818115","https://openalex.org/W4390906058","https://openalex.org/W4391324012","https://openalex.org/W4391693788","https://openalex.org/W4394004556","https://openalex.org/W4399404947","https://openalex.org/W4400450462","https://openalex.org/W4400595809","https://openalex.org/W4401163409","https://openalex.org/W4402027374","https://openalex.org/W4404035222","https://openalex.org/W4405717818","https://openalex.org/W4405869431","https://openalex.org/W4405974090","https://openalex.org/W4407143514","https://openalex.org/W4407299359","https://openalex.org/W4407449792","https://openalex.org/W4407690720","https://openalex.org/W4407923597","https://openalex.org/W4408157424","https://openalex.org/W4408564948","https://openalex.org/W4409378618","https://openalex.org/W4409568286","https://openalex.org/W4417288030","https://openalex.org/W7133188824"],"related_works":[],"abstract_inverted_index":{"Deep":[0],"learning":[1,158,211],"models":[2],"for":[3,126,266],"skeleton-based":[4],"Human":[5],"Activity":[6],"Recognition":[7],"(HAR)":[8],"routinely":[9],"exceed":[10],"93%":[11],"accuracy":[12],"on":[13,53,137,199],"controlled":[14],"benchmarks":[15],"such":[16],"as":[17,216],"NTU":[18],"RGB+D,":[19],"yet":[20],"degrade":[21],"by":[22,42],"30\u201360%":[23],"when":[24,54],"confronted":[25],"with":[26],"the":[27,68,200,204,217,268],"noise,":[28],"demographic":[29,113],"diversity,":[30],"and":[31,76,87,98,103,110,132,156,163,166,171,174,208,212,234,252,274],"environmental":[32],"variability":[33],"of":[34],"real-world":[35],"deployment.":[36],"Existing":[37],"surveys":[38],"catalog":[39],"this":[40],"progress":[41],"network":[43],"architecture":[44],"(RNNs,":[45],"CNNs,":[46],"GCNs,":[47],"Transformers)":[48],"but":[49],"provide":[50,176],"limited":[51],"guidance":[52],"or":[55,134],"why":[56],"one":[57],"approach":[58],"outperforms":[59],"another":[60],"under":[61,255],"specific":[62],"deployment":[63,79,223,240,257],"constraints.":[64],"This":[65],"survey":[66],"reframes":[67],"field":[69],"through":[70],"a":[71,138,230,235],"generalization-centered":[72],"lens.":[73],"We":[74,225],"identify":[75],"quantify":[77],"six":[78],"challenges":[80],"that":[81,186,195,209,238],"drive":[82],"performance":[83],"degradation:":[84],"sensor":[85],"noise":[86],"pose":[88],"estimation":[89],"errors":[90],"(46\u201360":[91],"percentage":[92],"point":[93],"gap":[94,270],"between":[95,108],"clean":[96],"Kinect":[97],"RGB-estimated":[99],"skeletons),":[100],"open":[101],"vocabulary":[102],"unseen":[104],"actions":[105],"(47\u201363":[106],"pp":[107,116],"supervised":[109,128],"zero-shot":[111],"results),":[112],"shift":[114],"(20\u201340":[115],"across":[117,221,271],"elderly-inclusive":[118],"benchmarks),":[119],"cross-dataset":[120],"transfer":[121],"(10\u201333":[122],"pp),":[123,131],"annotation":[124],"scarcity":[125],"purely":[127],"training":[129],"(10\u201315":[130],"cross-subject":[133],"cross-view":[135],"variation":[136],"single":[139],"dataset":[140],"(3\u20137":[141],"pp).":[142],"For":[143],"each":[144],"challenge,":[145],"we":[146,175],"systematically":[147],"evaluate":[148],"how":[149],"representation":[150],"paradigms":[151,220],"(sequential,":[152],"spatial,":[153],"graph,":[154],"attention,":[155],"cross-modal),":[157],"strategies":[159],"(self-supervised,":[160],"semi-supervised,":[161],"few-shot,":[162],"domain":[164],"adaptation),":[165],"integration":[167],"techniques":[168],"(fusion,":[169],"distillation,":[170],"multi-task)":[172],"perform,":[173],"cross-method":[177],"comparisons":[178],"grounded":[179],"in":[180],"published":[181],"results.":[182],"Our":[183],"analysis":[184],"shows":[185],"no":[187],"method":[188,243],"effectively":[189],"addresses":[190],"more":[191],"than":[192],"three":[193],"challenges,":[194],"research":[196,261],"effort":[197],"focuses":[198],"smallest":[201],"gaps":[202],"while":[203],"largest":[205],"remain":[206],"understudied,":[207],"self-supervised":[210],"CNN-based":[213],"representations":[214],"emerge":[215],"most":[218],"versatile":[219],"multiple":[222],"scenarios.":[224],"synthesize":[226],"these":[227],"findings":[228],"into":[229],"method\u2013challenge":[231],"suitability":[232],"matrix":[233],"decision":[236],"framework":[237],"links":[239],"constraints":[241],"to":[242],"recommendations.":[244],"These":[245],"recommendations":[246],"are":[247],"derived":[248],"from":[249],"single-challenge":[250],"evidence":[251],"require":[253],"validation":[254],"simultaneous-challenge":[256],"conditions.":[258],"A":[259],"three-tier":[260],"roadmap":[262],"identifies":[263],"concrete":[264],"directions":[265],"bridging":[267],"generalization":[269],"near-,":[272],"mid-,":[273],"long-term":[275],"horizons.":[276]},"counts_by_year":[],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2026-07-04T00:00:00"}