{"id":"https://openalex.org/W7154959619","doi":"https://doi.org/10.48550/arxiv.2604.16214","title":"GAViD: A Large-Scale Multimodal Dataset for Context-Aware Group Affect Recognition from Videos","display_name":"GAViD: A Large-Scale Multimodal Dataset for Context-Aware Group Affect Recognition from Videos","publication_year":2026,"publication_date":"2026-04-17","ids":{"openalex":"https://openalex.org/W7154959619","doi":"https://doi.org/10.48550/arxiv.2604.16214"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.16214","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.16214","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.16214","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100702995","display_name":"Deepak Kumar","orcid":"https://orcid.org/0000-0003-1263-0272"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kumar, Deepak","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134091309","display_name":"Abhishek Pratap Singh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Singh, Abhishek Pratap","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134085219","display_name":"Puneet Kumar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kumar, Puneet","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134006607","display_name":"Xiaobai Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Xiaobai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5030765476","display_name":"Balasubramanian Raman","orcid":"https://orcid.org/0000-0001-6277-6267"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Raman, Balasubramanian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9775999784469604,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9775999784469604,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.006500000134110451,"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/T10709","display_name":"Social Robot Interaction and HRI","score":0.002199999988079071,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/affect","display_name":"Affect (linguistics)","score":0.7207000255584717},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.5806999802589417},{"id":"https://openalex.org/keywords/affective-computing","display_name":"Affective computing","score":0.5602999925613403},{"id":"https://openalex.org/keywords/contextual-design","display_name":"Contextual design","score":0.46459999680519104},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.45260000228881836},{"id":"https://openalex.org/keywords/valence","display_name":"Valence (chemistry)","score":0.41609999537467957},{"id":"https://openalex.org/keywords/computational-sociology","display_name":"Computational sociology","score":0.35850000381469727}],"concepts":[{"id":"https://openalex.org/C2776035688","wikidata":"https://www.wikidata.org/wiki/Q1606558","display_name":"Affect (linguistics)","level":2,"score":0.7207000255584717},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7156999707221985},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.5806999802589417},{"id":"https://openalex.org/C6438553","wikidata":"https://www.wikidata.org/wiki/Q1185804","display_name":"Affective computing","level":2,"score":0.5602999925613403},{"id":"https://openalex.org/C71611378","wikidata":"https://www.wikidata.org/wiki/Q5165191","display_name":"Contextual design","level":3,"score":0.46459999680519104},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.45260000228881836},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44769999384880066},{"id":"https://openalex.org/C168900304","wikidata":"https://www.wikidata.org/wiki/Q171407","display_name":"Valence (chemistry)","level":2,"score":0.41609999537467957},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3885999917984009},{"id":"https://openalex.org/C126349790","wikidata":"https://www.wikidata.org/wiki/Q905036","display_name":"Computational sociology","level":2,"score":0.35850000381469727},{"id":"https://openalex.org/C135641252","wikidata":"https://www.wikidata.org/wiki/Q738567","display_name":"Multimodal interaction","level":2,"score":0.3314000070095062},{"id":"https://openalex.org/C2780910867","wikidata":"https://www.wikidata.org/wiki/Q1952416","display_name":"Multimodality","level":2,"score":0.3138999938964844},{"id":"https://openalex.org/C130064352","wikidata":"https://www.wikidata.org/wiki/Q853725","display_name":"Social relation","level":2,"score":0.3100999891757965},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.30059999227523804},{"id":"https://openalex.org/C194995250","wikidata":"https://www.wikidata.org/wiki/Q531136","display_name":"Affordance","level":2,"score":0.29829999804496765},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.29179999232292175},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2874000072479248},{"id":"https://openalex.org/C2781311116","wikidata":"https://www.wikidata.org/wiki/Q83306","display_name":"Group (periodic table)","level":2,"score":0.25380000472068787}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.16214","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.16214","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.16214","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.16214","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6513473987579346,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Understanding":[0],"affective":[1],"dynamics":[2],"in":[3,15,46,85],"real-world":[4],"social":[5,37,63],"systems":[6,38],"is":[7],"fundamental":[8],"to":[9,52,152],"modeling":[10,33,42],"and":[11,27,57,68,79,109,115,119,125,157],"analyzing":[12],"human-human":[13,23],"interactions":[14,64],"complex":[16],"environments.":[17],"Group":[18,94,133],"affect":[19,45,142],"emerges":[20],"from":[21,96],"intertwined":[22],"interactions,":[24],"contextual":[25,67,80,123],"influences,":[26],"behavioral":[28,69],"cues,":[29],"making":[30],"its":[31],"quantitative":[32],"a":[34],"challenging":[35,50],"computational":[36,41],"problem.":[39],"However,":[40],"of":[43,61,73],"group":[44,141],"in-the-wild":[47],"scenarios":[48],"remains":[49],"due":[51],"limited":[53],"large-scale":[54],"annotated":[55,76,111],"datasets":[56,75],"the":[58,86,93],"inherent":[59],"complexity":[60],"multimodal":[62,78,105,139],"shaped":[65],"by":[66],"variability.":[70],"The":[71,155],"lack":[72],"comprehensive":[74],"with":[77,104,112,121],"information":[81],"further":[82],"limits":[83],"advances":[84],"field.":[87],"To":[88],"address":[89],"this,":[90],"we":[91],"introduce":[92],"Affect":[95,134],"ViDeos":[97],"(GAViD)":[98],"dataset,":[99],"comprising":[100],"5091":[101],"video":[102],"clips":[103],"data":[106],"(video,":[107],"audio":[108],"context),":[110],"ternary":[113],"valence":[114],"discrete":[116],"emotion":[117],"labels":[118],"enriched":[120],"VideoGPT-generated":[122],"metadata":[124],"human-annotated":[126],"action":[127],"cues.":[128],"We":[129],"also":[130],"present":[131],"Context-Aware":[132],"Recognition":[135],"Network":[136],"(CAGNet)":[137],"for":[138],"context-aware":[140],"recognition.":[143],"CAGNet":[144],"achieves":[145],"63.20\\%":[146],"test":[147],"accuracy":[148],"on":[149],"GAViD,":[150],"comparable":[151],"state-of-the-art":[153],"performance.":[154],"dataset":[156],"code":[158],"are":[159],"available":[160],"at":[161],"github.com/deepakkumar-iitr/GAViD.":[162]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-21T00:00:00"}
