{"id":"https://openalex.org/W4391310489","doi":"https://doi.org/10.1145/3633624.3633635","title":"Integrating Dual-Stream Cross Fusion and Ambiguous Exclude Contrastive Learning for Enhanced Human Action Recognition","display_name":"Integrating Dual-Stream Cross Fusion and Ambiguous Exclude Contrastive Learning for Enhanced Human Action Recognition","publication_year":2023,"publication_date":"2023-10-20","ids":{"openalex":"https://openalex.org/W4391310489","doi":"https://doi.org/10.1145/3633624.3633635"},"language":"en","primary_location":{"id":"doi:10.1145/3633624.3633635","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3633624.3633635","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 5th International Conference on Big-data Service and Intelligent Computation","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/A5086479221","display_name":"Biaozhang Huang","orcid":"https://orcid.org/0009-0009-8628-5839"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Biaozhang Huang","raw_affiliation_strings":["Southeast University, China and Nanjing Center for Applied Mathematics, China"],"raw_orcid":"https://orcid.org/0009-0009-8628-5839","affiliations":[{"raw_affiliation_string":"Southeast University, China and Nanjing Center for Applied Mathematics, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010863275","display_name":"Xinde Li","orcid":"https://orcid.org/0000-0002-1529-4537"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinde Li","raw_affiliation_strings":["Southeast University, China and Nanjing Center for Applied Mathematics, China"],"raw_orcid":"https://orcid.org/0000-0002-1529-4537","affiliations":[{"raw_affiliation_string":"Southeast University, China and Nanjing Center for Applied Mathematics, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5086479221"],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18947561,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"75","last_page":"81"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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":0.9998999834060669,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9976000189781189,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9973000288009644,"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/dual","display_name":"Dual (grammatical number)","score":0.6703031659126282},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.655194878578186},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.5632209777832031},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48669081926345825},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.4700511693954468},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.45746973156929016},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3359767198562622},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.06859913468360901}],"concepts":[{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.6703031659126282},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.655194878578186},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.5632209777832031},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48669081926345825},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.4700511693954468},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.45746973156929016},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3359767198562622},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.06859913468360901},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3633624.3633635","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3633624.3633635","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 5th International Conference on Big-data Service and Intelligent Computation","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.41999998688697815}],"awards":[{"id":"https://openalex.org/G2124180530","display_name":null,"funder_award_id":"62233003, 62073072","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"}],"funders":[{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1483019628","https://openalex.org/W2034443282","https://openalex.org/W2048821851","https://openalex.org/W2054041160","https://openalex.org/W2145494108","https://openalex.org/W2212964709","https://openalex.org/W2293363371","https://openalex.org/W2738575313","https://openalex.org/W2798991696","https://openalex.org/W2847278683","https://openalex.org/W2908684875","https://openalex.org/W2909888383","https://openalex.org/W2948246283","https://openalex.org/W2956928039","https://openalex.org/W2963076818","https://openalex.org/W2964134613","https://openalex.org/W2964159205","https://openalex.org/W2981952041","https://openalex.org/W3035524453","https://openalex.org/W3092424783","https://openalex.org/W3093751392","https://openalex.org/W3105195350","https://openalex.org/W3127541398","https://openalex.org/W3160306726","https://openalex.org/W3185273257","https://openalex.org/W3199335549","https://openalex.org/W3203227473","https://openalex.org/W3205106480","https://openalex.org/W4200634815","https://openalex.org/W4221166048","https://openalex.org/W4285216227","https://openalex.org/W4309368547","https://openalex.org/W4312675926","https://openalex.org/W4313185874","https://openalex.org/W4324080648","https://openalex.org/W4367359578"],"related_works":["https://openalex.org/W2317351040","https://openalex.org/W4285447065","https://openalex.org/W2393949104","https://openalex.org/W1988622314","https://openalex.org/W2099421762","https://openalex.org/W3046201198","https://openalex.org/W2530546662","https://openalex.org/W1576128429","https://openalex.org/W2269464716","https://openalex.org/W2983481687"],"abstract_inverted_index":{"In":[0],"the":[1,8,56,66,82,86,116,135],"field":[2],"of":[3,11,65,96,137],"semi-supervised":[4],"human":[5],"action":[6],"recognition,":[7],"effective":[9],"utilization":[10],"both":[12],"labeled":[13],"and":[14,20,68,100,123,131],"unlabeled":[15],"data":[16],"remains":[17],"a":[18,35,92],"central":[19],"challenging":[21],"pursuit.":[22],"To":[23,79],"address":[24],"this":[25],"issue,":[26],"we":[27,84],"present":[28],"an":[29,42],"innovative":[30],"framework":[31],"(DSCF-AEC)":[32],"that":[33],"combines":[34],"Dual-stream":[36,51],"Cross":[37,52],"Fusion":[38,53],"network":[39,54],"(DSCF)":[40],"with":[41],"Ambiguous":[43],"Exclude":[44],"Contrastive":[45],"Learning":[46],"(AEC)":[47],"module.":[48,88],"Specifically,":[49],"our":[50,138,144],"utilizes":[55],"ST-GCN":[57],"as":[58],"encoder,":[59],"independently":[60],"encoding":[61],"two":[62],"augmented":[63],"versions":[64],"joint":[67],"bone":[69],"streams,":[70],"which":[71],"are":[72,106],"subsequently":[73],"cross-fused":[74],"to":[75],"achieve":[76],"enhanced":[77],"representation.":[78],"further":[80],"bolster":[81],"performance,":[83],"designed":[85],"AEC":[87],"This":[89,108],"module":[90],"constructs":[91],"memory":[93],"bank":[94],"capable":[95],"distinguishing":[97],"reliable":[98],"positive":[99],"negative":[101],"samples,":[102],"while":[103],"ambiguous":[104],"samples":[105],"excluded.":[107],"strategic":[109],"approach":[110],"ensures":[111],"that,":[112,143],"through":[113],"contrastive":[114],"learning,":[115],"model":[117],"is":[118],"trained":[119],"solely":[120],"on":[121,128],"meaningful":[122],"trustworthy":[124],"samples.":[125],"Extensive":[126],"experiments":[127],"NTU":[129],"RGB+D":[130],"NW-UCLA":[132],"datasets":[133],"validate":[134],"effectiveness":[136],"approach.":[139],"The":[140],"results":[141],"indicate":[142],"proposed":[145],"method":[146],"significantly":[147],"outperforms":[148],"other":[149],"existing":[150],"methods.":[151]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}