{"id":"https://openalex.org/W4405778915","doi":"https://doi.org/10.1109/tmm.2024.3521749","title":"GCN-Based Multi-Modality Fusion Network for Action Recognition","display_name":"GCN-Based Multi-Modality Fusion Network for Action Recognition","publication_year":2024,"publication_date":"2024-12-25","ids":{"openalex":"https://openalex.org/W4405778915","doi":"https://doi.org/10.1109/tmm.2024.3521749"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2024.3521749","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2024.3521749","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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5091894946","display_name":"Shaocan Liu","orcid":"https://orcid.org/0000-0002-3813-5547"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaocan Liu","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China"],"raw_orcid":"https://orcid.org/0000-0002-3813-5547","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022103187","display_name":"Xingtao Wang","orcid":"https://orcid.org/0000-0002-5763-2493"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingtao Wang","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China"],"raw_orcid":"https://orcid.org/0000-0002-5763-2493","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013727612","display_name":"Ruiqin Xiong","orcid":"https://orcid.org/0000-0001-9796-0478"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruiqin Xiong","raw_affiliation_strings":["School of Electronic Engineering and Computer Science, Institute of Digital Media, Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9796-0478","affiliations":[{"raw_affiliation_string":"School of Electronic Engineering and Computer Science, Institute of Digital Media, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079412089","display_name":"Xiaopeng Fan","orcid":"https://orcid.org/0000-0002-9660-3636"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaopeng Fan","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China"],"raw_orcid":"https://orcid.org/0000-0002-9660-3636","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2495,"currency":"USD","value_usd":2495},"apc_paid":null,"fwci":1.5252,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.83528177,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"27","issue":null,"first_page":"1242","last_page":"1253"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9943000078201294,"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":0.9943000078201294,"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":0.9577999711036682,"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":0.9333000183105469,"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/computer-science","display_name":"Computer science","score":0.8171041011810303},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.6226677298545837},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5279176235198975},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4589892327785492},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4573705494403839},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.4475557804107666},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.41702964901924133},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39617037773132324}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8171041011810303},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.6226677298545837},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5279176235198975},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4589892327785492},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4573705494403839},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.4475557804107666},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.41702964901924133},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39617037773132324},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2024.3521749","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2024.3521749","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5430980299","display_name":null,"funder_award_id":"U22B2035","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5887223637","display_name":null,"funder_award_id":"62441202","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":77,"referenced_works":["https://openalex.org/W1541521713","https://openalex.org/W1964357740","https://openalex.org/W2008824967","https://openalex.org/W2105101328","https://openalex.org/W2142194269","https://openalex.org/W2165715280","https://openalex.org/W2194775991","https://openalex.org/W2235034809","https://openalex.org/W2309561466","https://openalex.org/W2462996230","https://openalex.org/W2559833261","https://openalex.org/W2604321021","https://openalex.org/W2605111198","https://openalex.org/W2606294640","https://openalex.org/W2716916105","https://openalex.org/W2799211965","https://openalex.org/W2802503116","https://openalex.org/W2802979841","https://openalex.org/W2868292291","https://openalex.org/W2894879265","https://openalex.org/W2897506137","https://openalex.org/W2940457086","https://openalex.org/W2944006115","https://openalex.org/W2945143046","https://openalex.org/W2948058585","https://openalex.org/W2953787907","https://openalex.org/W2963076818","https://openalex.org/W2963082988","https://openalex.org/W2963091558","https://openalex.org/W2963282966","https://openalex.org/W2963465695","https://openalex.org/W2963526497","https://openalex.org/W2963901033","https://openalex.org/W2964134613","https://openalex.org/W2981923053","https://openalex.org/W2982083293","https://openalex.org/W2986953233","https://openalex.org/W2994857106","https://openalex.org/W2996249958","https://openalex.org/W2996835428","https://openalex.org/W2997769980","https://openalex.org/W3003423830","https://openalex.org/W3016234935","https://openalex.org/W3034999503","https://openalex.org/W3035050855","https://openalex.org/W3035149912","https://openalex.org/W3035225512","https://openalex.org/W3047772167","https://openalex.org/W3092754310","https://openalex.org/W3093411241","https://openalex.org/W3093751392","https://openalex.org/W3108496296","https://openalex.org/W3109392981","https://openalex.org/W3119381934","https://openalex.org/W3156800342","https://openalex.org/W3165978997","https://openalex.org/W3174836262","https://openalex.org/W3177052299","https://openalex.org/W3185273257","https://openalex.org/W3203634062","https://openalex.org/W3205730621","https://openalex.org/W3209114016","https://openalex.org/W3209892011","https://openalex.org/W3213518743","https://openalex.org/W3215030504","https://openalex.org/W4214614183","https://openalex.org/W4225650823","https://openalex.org/W4282981352","https://openalex.org/W4296438114","https://openalex.org/W4312245820","https://openalex.org/W4312638762","https://openalex.org/W4312757006","https://openalex.org/W4319993407","https://openalex.org/W4385245566","https://openalex.org/W6735888532","https://openalex.org/W6746023985","https://openalex.org/W6799178971"],"related_works":["https://openalex.org/W2385859805","https://openalex.org/W2530972254","https://openalex.org/W2374013449","https://openalex.org/W73545470","https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W3214791684","https://openalex.org/W1576128429","https://openalex.org/W2152662039","https://openalex.org/W2269464716"],"abstract_inverted_index":{"Thanks":[0],"to":[1,29,39,92,120,143,176,201],"the":[2,55,63,66,156,172,183,202,217,223],"remarkably":[3],"expressive":[4],"power":[5],"for":[6,18,195],"depicting":[7],"structural":[8],"data,":[9],"Graph":[10],"Convolutional":[11],"Network":[12,90],"(GCN)":[13],"has":[14],"been":[15],"extensively":[16],"adopted":[17],"skeleton-based":[19],"action":[20,198],"recognition":[21],"in":[22,62,97,164],"recent":[23],"years.":[24],"However,":[25],"GCN":[26,75],"is":[27,103,119,141,152,193],"designed":[28,142],"operate":[30],"on":[31,45,229],"irregular":[32],"graphs":[33],"of":[34,57,68,234],"skeletons,":[35],"making":[36],"it":[37],"difficult":[38],"deal":[40],"with":[41,110,155],"other":[42,71],"modalities":[43,72],"represented":[44],"regular":[46],"grids":[47],"directly.":[48],"Thus,":[49],"although":[50],"existing":[51],"works":[52],"have":[53],"demonstrated":[54],"necessity":[56],"multi-modality":[58,113],"fusion,":[59],"few":[60],"methods":[61],"literature":[64],"explore":[65],"fusion":[67,114,162,167],"skeleton":[69,100,157],"and":[70,99,124,131,181,214,238],"within":[73,209],"a":[74,82,107,111,136,160,188],"architecture.":[76],"In":[77,186],"this":[78],"paper,":[79],"we":[80],"present":[81],"novel":[83],"GCN-based":[84,87,112],"framework,":[85],"termed":[86],"Multi-modality":[88],"Fusion":[89],"(GMFNet),":[91],"efficiently":[93],"utilize":[94],"complementary":[95],"information":[96,127],"RGB":[98,132,146],"data.":[101],"GMFNet":[102,205,225],"constructed":[104],"by":[105],"connecting":[106],"main":[108,174],"stream":[109,175],"module":[115],"(GMFM),":[116],"whose":[117],"goal":[118],"gradually":[121],"combine":[122],"finer":[123],"coarse":[125],"action-related":[126],"extracted":[128],"from":[129],"skeletons":[130],"videos,":[133],"respectively.":[134],"Specifically,":[135],"cross-modality":[137],"data":[138,232],"mapping":[139],"method":[140],"transform":[144],"an":[145,210],"video":[147],"into":[148,171],"a$\\mathit{skeleton-like}$(SL)":[149],"sequence,":[150],"which":[151],"then":[153],"integrated":[154],"sequence":[158],"under":[159],"gradual":[161],"scheme":[163],"GMFM.":[165],"The":[166],"results":[168,221],"are":[169],"fed":[170],"following":[173],"extract":[177],"more":[178,196],"discriminative":[179],"features":[180],"produce":[182],"final":[184],"prediction.":[185],"addition,":[187],"spatio-temporal":[189],"joint":[190],"attention":[191],"mechanism":[192],"introduced":[194],"accurate":[197],"recognition.":[199],"Compared":[200],"multi-stream":[203],"approaches,":[204],"can":[206],"be":[207],"implemented":[208],"end-to-end":[211],"training":[212,218],"pipeline":[213],"thereby":[215],"reduces":[216],"complexity.":[219],"Experimental":[220],"show":[222],"proposed":[224],"achieves":[226],"impressive":[227],"performance":[228],"two":[230],"large-scale":[231],"sets":[233],"NTU":[235],"RGB+D":[236],"60":[237],"120.":[239]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":6}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}