{"id":"https://openalex.org/W3092961189","doi":"https://doi.org/10.1145/3394171.3416281","title":"Learning to Remember Beauty Products","display_name":"Learning to Remember Beauty Products","publication_year":2020,"publication_date":"2020-10-12","ids":{"openalex":"https://openalex.org/W3092961189","doi":"https://doi.org/10.1145/3394171.3416281","mag":"3092961189"},"language":"en","primary_location":{"id":"doi:10.1145/3394171.3416281","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3416281","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Multimedia","raw_type":"proceedings-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/A5028497212","display_name":"Toan H. Vu","orcid":"https://orcid.org/0000-0001-8775-120X"},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Toan H. Vu","raw_affiliation_strings":["National Central University, Taoyuan, Taiwan Roc"],"affiliations":[{"raw_affiliation_string":"National Central University, Taoyuan, Taiwan Roc","institution_ids":["https://openalex.org/I22265921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084701593","display_name":"An Dang","orcid":"https://orcid.org/0009-0000-2518-7180"},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"An Dang","raw_affiliation_strings":["National Central University, Taoyuan, Taiwan Roc"],"affiliations":[{"raw_affiliation_string":"National Central University, Taoyuan, Taiwan Roc","institution_ids":["https://openalex.org/I22265921"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029325015","display_name":"Jia\u2010Ching Wang","orcid":"https://orcid.org/0000-0003-0024-6732"},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]},{"id":"https://openalex.org/I4210149422","display_name":"Pervasive Artificial Intelligence Research Labs","ror":"https://ror.org/05qjw7v53","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210149422"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jia-Ching Wang","raw_affiliation_strings":["National Central University & Pervasive Artificial Intelligence Research (PAIR) Labs, Taoyuan, Taiwan Roc"],"affiliations":[{"raw_affiliation_string":"National Central University & Pervasive Artificial Intelligence Research (PAIR) Labs, Taoyuan, Taiwan Roc","institution_ids":["https://openalex.org/I22265921","https://openalex.org/I4210149422"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5028497212"],"corresponding_institution_ids":["https://openalex.org/I22265921"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.11223701,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"4728","last_page":"4732"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9994000196456909,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9994000196456909,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9991000294685364,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9912999868392944,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8379904627799988},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6997287273406982},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6926438212394714},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6729761362075806},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6654623746871948},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6152687072753906},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5968350172042847},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.581663966178894},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5550609827041626},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5386289358139038},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.49843645095825195},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4793318510055542},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.47222021222114563},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4433111548423767},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.4353821873664856},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.34455329179763794},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33880674839019775}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8379904627799988},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6997287273406982},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6926438212394714},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6729761362075806},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6654623746871948},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6152687072753906},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5968350172042847},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.581663966178894},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5550609827041626},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5386289358139038},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.49843645095825195},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4793318510055542},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.47222021222114563},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4433111548423767},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.4353821873664856},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.34455329179763794},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33880674839019775},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3394171.3416281","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3416281","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7300000190734863}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1532499126","https://openalex.org/W1861492603","https://openalex.org/W2096733369","https://openalex.org/W2100398441","https://openalex.org/W2100799972","https://openalex.org/W2108598243","https://openalex.org/W2295537791","https://openalex.org/W2520774990","https://openalex.org/W2584637367","https://openalex.org/W2896426063","https://openalex.org/W2897712612","https://openalex.org/W2953044442","https://openalex.org/W2963129433","https://openalex.org/W2963446712","https://openalex.org/W2963588253","https://openalex.org/W2981448404","https://openalex.org/W2981517406","https://openalex.org/W2981692745","https://openalex.org/W2982174019","https://openalex.org/W2998621280","https://openalex.org/W3099206234","https://openalex.org/W4299653752"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2129146436","https://openalex.org/W2032507829","https://openalex.org/W3119773509","https://openalex.org/W3208297503","https://openalex.org/W2889153461","https://openalex.org/W2964117661","https://openalex.org/W4388405611","https://openalex.org/W2619127353"],"abstract_inverted_index":{"This":[0],"paper":[1],"develops":[2],"a":[3,24,33,53,103,143],"deep":[4,34],"learning":[5],"model":[6,16,118,141],"for":[7],"the":[8,46,99,111,132,136,139],"beauty":[9],"product":[10],"image":[11],"retrieval":[12,145],"problem.":[13],"The":[14,26,76],"proposed":[15,140],"has":[17],"two":[18],"main":[19],"components-":[20],"an":[21,49],"encoder":[22,27,112],"and":[23,29,52,64,89,127],"memory.":[25],"extracts":[28],"aggregates":[30],"features":[31],"from":[32,110],"convolutional":[35],"neural":[36],"network":[37],"at":[38],"multiple":[39],"scales":[40],"to":[41,59,106,113],"get":[42],"feature":[43,125],"embeddings.":[44],"With":[45],"use":[47],"of":[48,79,82,138],"attention":[50],"mechanism":[51],"data":[54],"augmentation":[55],"method,":[56],"it":[57,71,90],"learns":[58],"focus":[60],"on":[61,67,98,131],"foreground":[62],"objects":[63],"neglect":[65],"background":[66],"images,":[68],"so":[69],"can":[70,91],"extract":[72],"more":[73,115],"relevant":[74],"features.":[75],"memory":[77],"consists":[78],"representative":[80],"states":[81],"all":[83],"database":[84],"images":[85],"as":[86],"its":[87],"stacks,":[88],"be":[92,114],"updated":[93],"during":[94],"training":[95],"process.":[96],"Based":[97],"memory,":[100],"we":[101],"introduce":[102],"distance":[104],"loss":[105],"regularize":[107],"embedding":[108],"vectors":[109],"discriminative.":[116],"Our":[117],"is":[119],"fully":[120],"end-to-end,":[121],"requires":[122],"no":[123],"manual":[124],"aggregation":[126],"post-processing.":[128],"Experimental":[129],"results":[130],"Perfect-500K":[133],"dataset":[134],"demonstrate":[135],"effectiveness":[137],"with":[142],"significant":[144],"accuracy.":[146]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}