{"id":"https://openalex.org/W4304084144","doi":"https://doi.org/10.1145/3503161.3548408","title":"Robust Actor Recognition in Entertainment Multimedia at Scale","display_name":"Robust Actor Recognition in Entertainment Multimedia at Scale","publication_year":2022,"publication_date":"2022-10-10","ids":{"openalex":"https://openalex.org/W4304084144","doi":"https://doi.org/10.1145/3503161.3548408"},"language":"en","primary_location":{"id":"doi:10.1145/3503161.3548408","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3503161.3548408","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3503161.3548408","source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3503161.3548408","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068227018","display_name":"Abhinav Aggarwal","orcid":"https://orcid.org/0000-0002-5080-6390"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Abhinav Aggarwal","raw_affiliation_strings":["Amazon, Bengaluru, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Amazon, Bengaluru, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063640530","display_name":"Yash Pandya","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yash Pandya","raw_affiliation_strings":["Amazon, Bengaluru, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Amazon, Bengaluru, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059102011","display_name":"Lokesh A. Ravindranathan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lokesh A. Ravindranathan","raw_affiliation_strings":["Twitter, Bengaluru, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Twitter, Bengaluru, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032688412","display_name":"Laxmi S. Ahire","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Laxmi S. Ahire","raw_affiliation_strings":["Amazon, Bengaluru, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Amazon, Bengaluru, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049510592","display_name":"Manivel Sethu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Manivel Sethu","raw_affiliation_strings":["Amazon, Bengaluru, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Amazon, Bengaluru, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084546291","display_name":"Kaustav Nandy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kaustav Nandy","raw_affiliation_strings":["Amazon, Bengaluru, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Amazon, Bengaluru, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2359,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.58160006,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2079","last_page":"2087"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9997000098228455,"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/T11448","display_name":"Face recognition and analysis","score":0.9997000098228455,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9904000163078308,"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/T12290","display_name":"Human Motion and Animation","score":0.9800999760627747,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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":0.8063348531723022},{"id":"https://openalex.org/keywords/entertainment","display_name":"Entertainment","score":0.6500610113143921},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6118465662002563},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5434896945953369},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4525713622570038},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.451539546251297},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44543012976646423},{"id":"https://openalex.org/keywords/entertainment-industry","display_name":"Entertainment industry","score":0.44114911556243896},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3606981635093689},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.35254019498825073},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.09813272953033447}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8063348531723022},{"id":"https://openalex.org/C512170562","wikidata":"https://www.wikidata.org/wiki/Q173799","display_name":"Entertainment","level":2,"score":0.6500610113143921},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6118465662002563},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5434896945953369},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4525713622570038},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.451539546251297},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44543012976646423},{"id":"https://openalex.org/C2985708247","wikidata":"https://www.wikidata.org/wiki/Q173799","display_name":"Entertainment industry","level":3,"score":0.44114911556243896},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3606981635093689},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.35254019498825073},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.09813272953033447},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3503161.3548408","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3503161.3548408","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3503161.3548408","source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3503161.3548408","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3503161.3548408","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3503161.3548408","source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Multimedia","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4304084144.pdf","grobid_xml":"https://content.openalex.org/works/W4304084144.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W1986414721","https://openalex.org/W2019464758","https://openalex.org/W2096733369","https://openalex.org/W2155162820","https://openalex.org/W2165307239","https://openalex.org/W2168996682","https://openalex.org/W2169827072","https://openalex.org/W2319305483","https://openalex.org/W2341251094","https://openalex.org/W2341528187","https://openalex.org/W2907863735","https://openalex.org/W2957744218","https://openalex.org/W2969985801","https://openalex.org/W2981302199","https://openalex.org/W2982437619","https://openalex.org/W2982673782","https://openalex.org/W2997591727","https://openalex.org/W3101998545","https://openalex.org/W6600627465"],"related_works":["https://openalex.org/W2380636257","https://openalex.org/W3021794682","https://openalex.org/W2153470424","https://openalex.org/W2362084051","https://openalex.org/W2317673827","https://openalex.org/W2749121061","https://openalex.org/W2898918333","https://openalex.org/W1717474147","https://openalex.org/W2514454614","https://openalex.org/W4388813356"],"abstract_inverted_index":{"Actor":[0],"identification":[1,19],"and":[2,6,20,39,85,202,208,233],"localization":[3],"in":[4,25,56,145,169,230],"movies":[5,203,232],"TV":[7,162,200,234],"series":[8,163,235],"seasons":[9,116,236],"can":[10,94],"enable":[11],"deeper":[12],"engagement":[13],"with":[14,59,97,117,210],"the":[15,57,98,125,132,136,146,151,159,175,178,182,187],"content.":[16,128],"Manual":[17],"actor":[18,60,99,108],"tagging":[21],"at":[22],"every":[23],"time-instance":[24],"a":[26,34,67,73,170,224],"video":[27,58],"is":[28,33,47,112,180,186],"error":[29],"prone":[30],"as":[31,51,54],"it":[32],"highly":[35],"repetitive,":[36],"decision":[37],"intensive":[38],"time-consuming":[40],"task.":[41],"The":[42,220],"goal":[43],"of":[44,75,81,124,154,212],"this":[45,64],"paper":[46],"to":[48,106,142,161,177],"accurately":[49],"label":[50],"many":[52],"faces":[53,144],"possible":[55],"names.":[61],"We":[62,149],"solve":[63],"problem":[65],"using":[66],"multi-step":[68],"clustering":[69],"process":[70],"followed":[71],"by":[72,101,237],"selection":[74],"face-instances":[76,93],"that":[77],"are:":[78],"(a)":[79],"representative":[80],"their":[82],"member":[83],"clusters":[84],"(b)":[86],"aesthetically":[87],"pleasing":[88],"for":[89,115,227],"visual":[90],"identification.":[91],"These":[92],"be":[95],"matched":[96],"names":[100],"automated":[102],"or":[103],"manual":[104],"techniques":[105],"complete":[107],"tagging.":[109],"This":[110,165,185],"solution":[111,160,167,179,222],"further":[113],"optimized":[114],"repeating":[118],"cast":[119],"members":[120],"which":[121,191],"constitutes":[122],"majority":[123],"entertainment":[126],"multimedia":[127],"In":[129],"such":[130],"titles,":[131],"face":[133],"labels":[134],"from":[135],"previous":[137],"episodes":[138,201],"are":[139],"efficiently":[140],"used":[141],"pre-label":[143],"subsequent":[147],"episode.":[148],"guarantee":[150],"same":[152],"level":[153],"accuracy":[155],"even":[156],"after":[157],"scaling":[158],"seasons.":[164],"novel":[166],"works":[168],"completely":[171],"realistic":[172],"setup":[173],"where":[174],"input":[176],"just":[181],"raw":[183],"video.":[184],"first":[188],"known":[189],"work":[190],"has":[192],"proved":[193],"its":[194],"robustness":[195],"on":[196],"more":[197],"than":[198],"5000":[199],"across":[204],"different":[205],"genres,":[206],"languages":[207],"runtimes":[209],"actors":[211],"diverse":[213],"ethnicity,":[214],"race,":[215],"gender":[216],"identity,":[217],"age,":[218],"etc.":[219],"proposed":[221],"establishes":[223],"new":[225],"state-of-the-art":[226],"cluster":[228,240],"purity":[229],"both":[231],"achieving":[238],"near-perfect":[239],"homogeneity.":[241]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
