{"id":"https://openalex.org/W2765876634","doi":"https://doi.org/10.1145/3123266.3123441","title":"Understanding Fashion Trends from Street Photos via Neighbor-Constrained Embedding Learning","display_name":"Understanding Fashion Trends from Street Photos via Neighbor-Constrained Embedding Learning","publication_year":2017,"publication_date":"2017-10-19","ids":{"openalex":"https://openalex.org/W2765876634","doi":"https://doi.org/10.1145/3123266.3123441","mag":"2765876634"},"language":"en","primary_location":{"id":"doi:10.1145/3123266.3123441","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3123266.3123441","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th 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/A5022971426","display_name":"Xiaoling Gu","orcid":"https://orcid.org/0000-0002-2876-1771"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaoling Gu","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020006712","display_name":"Yongkang Wong","orcid":"https://orcid.org/0000-0002-1239-4428"},"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":"Yongkang Wong","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":"https://openalex.org/A5103110081","display_name":"Pai Peng","orcid":"https://orcid.org/0000-0002-7129-6174"},"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":"Pai Peng","raw_affiliation_strings":["Tencent Technology (Shanghai) Co., Ltd, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Tencent Technology (Shanghai) Co., Ltd, Shanghai, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103017455","display_name":"Lidan Shou","orcid":"https://orcid.org/0000-0001-8062-8356"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lidan Shou","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100389286","display_name":"Gang Chen","orcid":"https://orcid.org/0000-0002-7483-0045"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Chen","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016415049","display_name":"Mohan Kankanhalli","orcid":"https://orcid.org/0000-0002-4846-2015"},"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":"Mohan S. Kankanhalli","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"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5022971426"],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":1.2743,"has_fulltext":false,"cited_by_count":52,"citation_normalized_percentile":{"value":0.88118505,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"190","last_page":"198"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9970999956130981,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9970999956130981,"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/T11448","display_name":"Face recognition and analysis","score":0.9847000241279602,"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/T12650","display_name":"Aesthetic Perception and Analysis","score":0.983299970626831,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.8056643009185791},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.7830464839935303},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7817249894142151},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5872405767440796},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5659587979316711},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5298041105270386},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5265179872512817},{"id":"https://openalex.org/keywords/trace","display_name":"TRACE (psycholinguistics)","score":0.5172144174575806},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.49950551986694336},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47924044728279114},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.45395582914352417},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.41896945238113403},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4000679850578308},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3268759250640869}],"concepts":[{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.8056643009185791},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.7830464839935303},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7817249894142151},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5872405767440796},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5659587979316711},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5298041105270386},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5265179872512817},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.5172144174575806},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.49950551986694336},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47924044728279114},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.45395582914352417},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.41896945238113403},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4000679850578308},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3268759250640869},{"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3123266.3123441","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3123266.3123441","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM international conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W21006490","https://openalex.org/W170967611","https://openalex.org/W181871703","https://openalex.org/W1503398984","https://openalex.org/W1514027499","https://openalex.org/W1576123718","https://openalex.org/W1686810756","https://openalex.org/W1877469910","https://openalex.org/W1908139891","https://openalex.org/W1949942966","https://openalex.org/W1975517671","https://openalex.org/W2021354639","https://openalex.org/W2021541806","https://openalex.org/W2030628044","https://openalex.org/W2038147967","https://openalex.org/W2047809566","https://openalex.org/W2052420655","https://openalex.org/W2074621908","https://openalex.org/W2076434944","https://openalex.org/W2096733369","https://openalex.org/W2118585731","https://openalex.org/W2121339428","https://openalex.org/W2130556178","https://openalex.org/W2135367695","https://openalex.org/W2138621090","https://openalex.org/W2145326909","https://openalex.org/W2155893237","https://openalex.org/W2187089797","https://openalex.org/W2200092826","https://openalex.org/W2205224283","https://openalex.org/W2463470988","https://openalex.org/W2466740836","https://openalex.org/W2523978282","https://openalex.org/W2536305071","https://openalex.org/W2547446130","https://openalex.org/W2950325406","https://openalex.org/W2962798895","https://openalex.org/W2963775347","https://openalex.org/W2964189431","https://openalex.org/W3098379913","https://openalex.org/W3099206234","https://openalex.org/W3104449587"],"related_works":["https://openalex.org/W2081900870","https://openalex.org/W3125011624","https://openalex.org/W1508631387","https://openalex.org/W2370917603","https://openalex.org/W2952760143","https://openalex.org/W2017776670","https://openalex.org/W2347897961","https://openalex.org/W2340870721","https://openalex.org/W2358318464","https://openalex.org/W2979236518"],"abstract_inverted_index":{"Driven":[0],"by":[1,49,67,143],"the":[2,139,152,155,162],"increasing":[3],"popular":[4],"image-dominated":[5],"social":[6],"networks,":[7],"such":[8],"as":[9,96,98],"Instagram,":[10],"Pinterest":[11],"and":[12,30,72,92,119,160,183],"Chictopica,":[13],"sharing":[14],"of":[15,154,165],"daily-life":[16],"street":[17,46,52,131],"photos":[18],"now":[19],"plays":[20],"an":[21,59],"influential":[22],"role":[23],"in":[24],"fashion":[25,28,47,53,163,185],"adoption":[26],"between":[27],"trend-setters":[29],"followers.":[31],"In":[32,147,173],"this":[33],"work,":[34],"we":[35,56,158,176],"propose":[36],"a":[37,83,99,126,144],"deep":[38],"learning":[39,43],"based":[40,62],"fine-grained":[41,116],"embedding":[42,64],"approach":[44],"for":[45,102,114],"analysis":[48],"leveraging":[50],"user-generated":[51],"data.":[54],"Specifically,":[55],"present":[57],"QuadNet,":[58],"effective":[60,113],"CNN":[61],"image":[63,120],"network":[65,142],"driven":[66],"both":[68,90,115],"multi-task":[69,130],"classification":[70,117],"loss":[71,78,86],"neighbor-constrained":[73],"similarity":[74],"loss.":[75],"The":[76,106],"latter":[77],"function":[79],"is":[80,112],"computed":[81],"with":[82],"novel":[84],"quadruplet":[85],"function,":[87],"which":[88],"considers":[89],"hard":[91],"soft":[93],"positive":[94],"neighbors":[95],"well":[97],"negative":[100],"neighbor":[101],"each":[103],"anchor":[104],"image.":[105],"embedded":[107],"feature":[108],"learned":[109,156],"from":[110,169],"co-optimization":[111],"task":[118],"retrieval":[121],"task.":[122],"Quantitative":[123],"evaluation":[124],"on":[125],"newly":[127],"collected":[128],"large-scale":[129],"photo":[132],"dataset":[133],"shows":[134],"that":[135],"our":[136,174],"QuadNet":[137],"outperforms":[138],"state-of-the-art":[140],"triplet":[141],"significant":[145],"margin.":[146],"order":[148],"to":[149,171,179],"further":[150],"evaluate":[151],"effectiveness":[153],"embedding,":[157],"analyze":[159],"trace":[161],"trends":[164],"New":[166],"York":[167],"City":[168],"2011":[170],"2016.":[172],"analysis,":[175],"are":[177],"able":[178],"identify":[180],"some":[181],"short-term":[182],"long-term":[184],"styles.":[186]},"counts_by_year":[{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
