{"id":"https://openalex.org/W2053110996","doi":"https://doi.org/10.1145/2733373.2806303","title":"Predicting Image Memorability by Multi-view Adaptive Regression","display_name":"Predicting Image Memorability by Multi-view Adaptive Regression","publication_year":2015,"publication_date":"2015-10-13","ids":{"openalex":"https://openalex.org/W2053110996","doi":"https://doi.org/10.1145/2733373.2806303","mag":"2053110996"},"language":"en","primary_location":{"id":"doi:10.1145/2733373.2806303","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2733373.2806303","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd ACM international conference on Multimedia","raw_type":"proceedings-article"},"type":"conference-paper","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/A5080495327","display_name":"Houwen Peng","orcid":"https://orcid.org/0000-0001-8544-8952"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Houwen Peng","raw_affiliation_strings":["Chinese Academy of Sciences & Temple University, Beijing, China","Chinese Academy of Sciences & Temple University, Beijing, China#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences & Temple University, Beijing, China","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"Chinese Academy of Sciences & Temple University, Beijing, China#TAB#","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100399824","display_name":"Kai Li","orcid":"https://orcid.org/0000-0001-8452-620X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Li","raw_affiliation_strings":["Chinese Academy of Sciences, Beijing, China","Chinese Academy of Sciences , Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"Chinese Academy of Sciences , Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109346446","display_name":"Bing Li","orcid":"https://orcid.org/0000-0002-5888-6735"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bing Li","raw_affiliation_strings":["Chinese Academy of Sciences, Beijing, China","Chinese Academy of Sciences , Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"Chinese Academy of Sciences , Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061469520","display_name":"Haibin Ling","orcid":"https://orcid.org/0000-0003-4094-8413"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haibin Ling","raw_affiliation_strings":["Temple University, Philadelphia, USA","Temple University, Philadelphia, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Temple University, Philadelphia, USA","institution_ids":["https://openalex.org/I84392919"]},{"raw_affiliation_string":"Temple University, Philadelphia, USA#TAB#","institution_ids":["https://openalex.org/I84392919"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100906938","display_name":"Weihua Xiong","orcid":"https://orcid.org/0009-0003-8192-8803"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weihua Xiong","raw_affiliation_strings":["Chinese Academy of Sciences, Beijing, China","Chinese Academy of Sciences , Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"Chinese Academy of Sciences , Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114549594","display_name":"Weiming Hu","orcid":"https://orcid.org/0000-0001-9237-8825"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiming Hu","raw_affiliation_strings":["Chinese Academy of Sciences, Beijing, China","Chinese Academy of Sciences , Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"Chinese Academy of Sciences , Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3505,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.89757037,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1147","last_page":"1150"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","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/T11605","display_name":"Visual Attention and Saliency Detection","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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.996999979019165,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9961000084877014,"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/computer-science","display_name":"Computer science","score":0.776862621307373},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7169961929321289},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6482291221618652},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6400700807571411},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5662187933921814},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.51735919713974},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5143274068832397},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.49971461296081543},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46204066276550293},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.43027615547180176},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41056400537490845},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12246322631835938}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.776862621307373},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7169961929321289},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6482291221618652},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6400700807571411},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5662187933921814},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.51735919713974},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5143274068832397},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.49971461296081543},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46204066276550293},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.43027615547180176},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41056400537490845},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12246322631835938},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2733373.2806303","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2733373.2806303","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd ACM international conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1477894522","display_name":"\u7f51\u7edc\u654f\u611f\u89c6\u9891\u8bc6\u522b\u7684\u5173\u952e\u95ee\u9898\u7814\u7a76","funder_award_id":"61472421","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2027922120","https://openalex.org/W2063794147","https://openalex.org/W2097430540","https://openalex.org/W2100549954","https://openalex.org/W2110628941","https://openalex.org/W2123020895","https://openalex.org/W2127553237","https://openalex.org/W2144502914","https://openalex.org/W2145201922","https://openalex.org/W2145962650","https://openalex.org/W2158155099","https://openalex.org/W2160915541","https://openalex.org/W2161969291","https://openalex.org/W2163352848","https://openalex.org/W2163862118","https://openalex.org/W2250542744","https://openalex.org/W2950602671","https://openalex.org/W6678463710"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W972276598","https://openalex.org/W2951187577","https://openalex.org/W4386564352","https://openalex.org/W2952668426"],"abstract_inverted_index":{"The":[0,60],"images":[1,31,50],"we":[2,40,103],"encounter":[3],"throughout":[4],"our":[5],"lives":[6],"make":[7],"different":[8],"impressions":[9],"on":[10,120],"us:":[11],"Some":[12],"are":[13,20],"remembered":[14],"at":[15],"first":[16],"glance,":[17],"while":[18],"others":[19],"forgotten.":[21],"This":[22],"phenomenon":[23],"is":[24],"caused":[25],"by":[26,33,51,73],"the":[27,42,47,114,121,126,129],"intrinsic":[28],"memorability":[29,48,71,136],"of":[30,44,49,67,76,86,128],"revealed":[32],"recent":[34],"studies":[35],"[5,6].":[36],"In":[37],"this":[38],"paper,":[39],"address":[41],"issue":[43],"automatically":[45],"estimating":[46],"proposing":[52],"a":[53,98],"novel":[54],"multi-view":[55,99],"adaptive":[56,91,95],"regression":[57],"(MAR)":[58],"model.":[59],"MAR":[61],"model":[62,131],"provides":[63],"an":[64,90,94,105],"effective":[65],"mapping":[66],"visual":[68],"features":[69],"to":[70,112],"scores":[72],"taking":[74],"advantage":[75],"robust":[77],"feature":[78,82],"selection":[79],"and":[80,97],"multiple":[81],"integration.":[83],"It":[84],"consists":[85],"three":[87],"major":[88],"components:":[89],"loss":[92],"function,":[93],"regularization":[96],"modeling":[100],"strategy.":[101],"Moreover,":[102],"design":[104],"alternating":[106],"direction":[107],"method":[108],"(ADM)":[109],"optimization":[110],"algorithm":[111],"solve":[113],"proposed":[115,130],"objective":[116],"function.":[117],"Experimental":[118],"results":[119],"MIT":[122],"benchmark":[123],"dataset":[124],"show":[125],"superiority":[127],"compared":[132],"with":[133],"existing":[134],"image":[135],"prediction":[137],"methods.":[138]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":2}],"updated_date":"2026-08-06T08:24:18.245995","created_date":"2025-10-10T00:00:00"}