{"id":"https://openalex.org/W2795799194","doi":"https://doi.org/10.1145/3184558.3186584","title":"Fine-grained Video Attractiveness Prediction Using Multimodal Deep Learning on a Large Real-world Dataset","display_name":"Fine-grained Video Attractiveness Prediction Using Multimodal Deep Learning on a Large Real-world Dataset","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2795799194","doi":"https://doi.org/10.1145/3184558.3186584","mag":"2795799194"},"language":"en","primary_location":{"id":"doi:10.1145/3184558.3186584","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3184558.3186584","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=3186584&type=pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"http://dl.acm.org/ft_gateway.cfm?id=3186584&type=pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Xinpeng Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xinpeng Chen","raw_affiliation_strings":["Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jingyuan Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Jingyuan Chen","raw_affiliation_strings":["National University of Singapore, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Lin Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Ma","raw_affiliation_strings":["Tencent AI Lab, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tencent AI Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jian Yao","orcid":null},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Yao","raw_affiliation_strings":["Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wei Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Liu","raw_affiliation_strings":["Tencent AI Lab, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tencent AI Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jiebo Luo","orcid":null},"institutions":[{"id":"https://openalex.org/I5388228","display_name":"University of Rochester","ror":"https://ror.org/022kthw22","country_code":"US","type":"education","lineage":["https://openalex.org/I5388228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiebo Luo","raw_affiliation_strings":["University of Rochester, Rochester, NY, USA"],"affiliations":[{"raw_affiliation_string":"University of Rochester, Rochester, NY, USA","institution_ids":["https://openalex.org/I5388228"]}]},{"author_position":"last","author":{"id":null,"display_name":"Tong Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Zhang","raw_affiliation_strings":["Tencent AI Lab, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tencent AI Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":0.6382,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.73696462,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"671","last_page":"678"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","score":0.9994999766349792,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9994999766349792,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.9933000206947327,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9873999953269958,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/attractiveness","display_name":"Attractiveness","score":0.7835000157356262},{"id":"https://openalex.org/keywords/online-video","display_name":"Online video","score":0.694599986076355},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5478000044822693},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5418999791145325},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5098999738693237},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.4555000066757202},{"id":"https://openalex.org/keywords/internet-video","display_name":"Internet video","score":0.4514000117778778}],"concepts":[{"id":"https://openalex.org/C31173074","wikidata":"https://www.wikidata.org/wiki/Q2632514","display_name":"Attractiveness","level":2,"score":0.7835000157356262},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7067999839782715},{"id":"https://openalex.org/C2988167200","wikidata":"https://www.wikidata.org/wiki/Q16885149","display_name":"Online video","level":2,"score":0.694599986076355},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5478000044822693},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5446000099182129},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5418999791145325},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5098999738693237},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.4555000066757202},{"id":"https://openalex.org/C2779789524","wikidata":"https://www.wikidata.org/wiki/Q16885149","display_name":"Internet video","level":3,"score":0.4514000117778778},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3675999939441681},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.3634999990463257},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.3465000092983246},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.2937999963760376},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.28130000829696655},{"id":"https://openalex.org/C2988634675","wikidata":"https://www.wikidata.org/wiki/Q34508","display_name":"Video recording","level":2,"score":0.2766999900341034},{"id":"https://openalex.org/C65483669","wikidata":"https://www.wikidata.org/wiki/Q3536669","display_name":"Video processing","level":2,"score":0.2709999978542328},{"id":"https://openalex.org/C3018412434","wikidata":"https://www.wikidata.org/wiki/Q7889","display_name":"Video game","level":2,"score":0.25200000405311584}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3184558.3186584","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3184558.3186584","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=3186584&type=pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1804.01373","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1804.01373","pdf_url":"https://arxiv.org/pdf/1804.01373","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-160561","is_oa":false,"landing_page_url":"http://repository.hkust.edu.hk/ir/Record/1783.1-160561","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference paper"}],"best_oa_location":{"id":"doi:10.1145/3184558.3186584","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3184558.3186584","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=3186584&type=pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2795799194.pdf","grobid_xml":"https://content.openalex.org/works/W2795799194.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W1211924006","https://openalex.org/W1927052826","https://openalex.org/W1959749536","https://openalex.org/W1996986760","https://openalex.org/W2010399676","https://openalex.org/W2016053056","https://openalex.org/W2037970810","https://openalex.org/W2039355801","https://openalex.org/W2060505035","https://openalex.org/W2097117768","https://openalex.org/W2126579184","https://openalex.org/W2133824856","https://openalex.org/W2134717257","https://openalex.org/W2148154194","https://openalex.org/W2150578721","https://openalex.org/W2163292664","https://openalex.org/W2183341477","https://openalex.org/W2250384498","https://openalex.org/W2524482439","https://openalex.org/W2741249238","https://openalex.org/W2963293463","https://openalex.org/W2964081807","https://openalex.org/W2964350391","https://openalex.org/W3125952634"],"related_works":[],"abstract_inverted_index":{"Nowadays,":[0],"billions":[1],"of":[2,16,44,76,117,132,146,154,157,159,249,261,274,283],"videos":[3,164],"are":[4,21,165],"online":[5,25],"ready":[6],"to":[7,49,66,213,226],"be":[8],"viewed":[9,23],"and":[10,142,174,193,201,246,269,279],"shared.":[11],"Among":[12],"an":[13,211],"enormous":[14],"volume":[15],"videos,":[17,155],"some":[18],"popular":[19,120],"ones":[20],"widely":[22],"by":[24,231],"users":[26],"while":[27,184],"the":[28,105,118,124,128,151,181,188,191,215,241,250,259,272,276,280,284],"majority":[29],"attract":[30,40],"little":[31],"attention.":[32],"Furthermore,":[33],"within":[34],"each":[35],"video,":[36],"different":[37,42,140,202,205,223,254,267,289],"segments":[38,75],"may":[39],"significantly":[41],"numbers":[43],"views.":[45],"This":[46],"phenomenon":[47],"leads":[48],"a":[50,89,143],"challenging":[51,90],"yet":[52],"important":[53],"problem,":[54],"namely":[55],"fine-grained":[56,71,107,216],"video":[57,64,68,74,108,121,147,182,199,217,228,235,251],"attractiveness":[58,69,109,183,200,218,229],"prediction,":[59],"which":[60,112],"only":[61],"relies":[62],"on":[63,234],"contents":[65,252],"forecast":[67],"at":[70,253,288],"levels,":[72],"specifically":[73],"several":[77],"second":[78],"length":[79],"in":[80,123],"this":[81,101],"paper.":[82],"However,":[83],"one":[84,116],"major":[85],"obstacle":[86],"for":[87],"such":[88,168],"problem":[91],"is":[92,113],"that":[93,198],"no":[94],"suitable":[95],"benchmark":[96],"dataset":[97,110],"currently":[98],"exists.":[99],"To":[100],"end,":[102],"we":[103,196],"construct":[104],"first":[106],"(FVAD),":[111],"collected":[114],"from":[115,150],"most":[119],"websites":[122],"world.":[125],"In":[126],"total,":[127],"constructed":[129],"FVAD":[130,208],"consists":[131],"1,019":[133],"drama":[134],"episodes":[135],"with":[136,266],"780.6":[137],"hours":[138],"covering":[139],"categories":[141],"wide":[144],"variety":[145],"contents.":[148,236],"Apart":[149],"large":[152],"amount":[153],"hundreds":[156],"millions":[158],"user":[160],"behaviors":[161,282],"during":[162],"watching":[163],"also":[166],"included,":[167],"as":[169],"view":[170],"counts,":[171],"\"fast-forward,":[172],"\"fast-rewind,":[173],"so":[175],"on,":[176],"where":[177],"\"view":[178],"counts\"":[179],"reflects":[180],"other":[185],"engagements":[186,203],"capture":[187],"interactions":[189],"between":[190,244],"viewers":[192],"videos.":[194],"First,":[195],"demonstrate":[197,258],"present":[204],"relationships.":[206],"Second,":[207],"provides":[209],"us":[210],"opportunity":[212],"study":[214],"prediction":[219,230,286],"problem.":[220],"We":[221],"design":[222],"sequential":[224,238,264,285],"models":[225,239,265,287],"perform":[227],"relying":[232],"solely":[233],"The":[237],"exploit":[240],"multimodal":[242],"relationships":[243],"visual":[245,268],"audio":[247,270],"components":[248],"levels.":[255,290],"Experimental":[256],"results":[257],"effectiveness":[260],"our":[262],"proposed":[263],"representations,":[271],"necessity":[273],"incorporating":[275],"two":[277],"modalities,":[278],"complementary":[281]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":4}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2018-04-13T00:00:00"}