{"id":"https://openalex.org/W2409897154","doi":"https://doi.org/10.1145/2911996.2912002","title":"Matching User Photos to Online Products with Robust Deep Features","display_name":"Matching User Photos to Online Products with Robust Deep Features","publication_year":2016,"publication_date":"2016-06-06","ids":{"openalex":"https://openalex.org/W2409897154","doi":"https://doi.org/10.1145/2911996.2912002","mag":"2409897154"},"language":"en","primary_location":{"id":"doi:10.1145/2911996.2912002","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2911996.2912002","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2016 ACM on International Conference on Multimedia Retrieval","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/A5100442264","display_name":"Xi Wang","orcid":"https://orcid.org/0000-0002-5632-3146"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xi Wang","raw_affiliation_strings":["Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060685444","display_name":"Zhenfeng Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenfeng Sun","raw_affiliation_strings":["Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100669255","display_name":"Wenqiang Zhang","orcid":"https://orcid.org/0000-0002-3339-8751"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenqiang Zhang","raw_affiliation_strings":["Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016175345","display_name":"Yu Zhou","orcid":"https://orcid.org/0000-0003-4188-9953"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Zhou","raw_affiliation_strings":["Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047962986","display_name":"Yu\u2013Gang Jiang","orcid":"https://orcid.org/0000-0002-1907-8567"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu-Gang Jiang","raw_affiliation_strings":["Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100442264"],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":6.0122,"has_fulltext":false,"cited_by_count":58,"citation_normalized_percentile":{"value":0.97680702,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"7","last_page":"14"},"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":0.9998000264167786,"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":0.9998000264167786,"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":0.9976000189781189,"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":0.9966999888420105,"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":0.8500241041183472},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6538488268852234},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5645010471343994},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5514534115791321},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.542003333568573},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5289732813835144},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5190585255622864},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.49073541164398193},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.48067745566368103},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4795420169830322},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.4261210262775421},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.406690776348114},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06784752011299133}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8500241041183472},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6538488268852234},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5645010471343994},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5514534115791321},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.542003333568573},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5289732813835144},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5190585255622864},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.49073541164398193},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.48067745566368103},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4795420169830322},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.4261210262775421},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.406690776348114},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06784752011299133},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2911996.2912002","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2911996.2912002","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2016 ACM on International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5199999809265137}],"awards":[{"id":"https://openalex.org/G3368050527","display_name":null,"funder_award_id":"16QA1400500","funder_id":"https://openalex.org/F4320321885","funder_display_name":"Science and Technology Commission of Shanghai Municipality"},{"id":"https://openalex.org/G589637999","display_name":null,"funder_award_id":"61572134","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"},{"id":"https://openalex.org/F4320321885","display_name":"Science and Technology Commission of Shanghai Municipality","ror":"https://ror.org/03kt66j61"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1532499126","https://openalex.org/W1546430343","https://openalex.org/W2020969339","https://openalex.org/W2021354639","https://openalex.org/W2022508996","https://openalex.org/W2026014384","https://openalex.org/W2062118960","https://openalex.org/W2095569536","https://openalex.org/W2097117768","https://openalex.org/W2108598243","https://openalex.org/W2117539524","https://openalex.org/W2129305389","https://openalex.org/W2135367695","https://openalex.org/W2138621090","https://openalex.org/W2143183660","https://openalex.org/W2155541015","https://openalex.org/W2157364932","https://openalex.org/W2161565164","https://openalex.org/W2163605009","https://openalex.org/W2170881581","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2200092826","https://openalex.org/W2344188636","https://openalex.org/W2559655401","https://openalex.org/W2604272474","https://openalex.org/W2613718673","https://openalex.org/W2949117887","https://openalex.org/W2953106684","https://openalex.org/W3008672977","https://openalex.org/W3206507930","https://openalex.org/W6632543029"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W4230611425","https://openalex.org/W2731899572","https://openalex.org/W1972035260","https://openalex.org/W4304166257","https://openalex.org/W4294635752","https://openalex.org/W4383066092","https://openalex.org/W3048601286","https://openalex.org/W2965925734"],"abstract_inverted_index":{"This":[0],"paper":[1],"focuses":[2],"on":[3,131,177],"a":[4,11,81,138,146,202],"practically":[5],"very":[6,198],"important":[7],"problem":[8],"of":[9,79,112],"matching":[10],"real-world":[12,180],"product":[13,47,101],"photo":[14,159],"to":[15,89,134,144,171,197],"exactly":[16],"the":[17,30,34,46,66,77,91,95,99,113,129,156,167,173,185,190],"same":[18],"item(s)":[19],"in":[20,36,42,49,118],"online":[21,50,100],"shopping":[22],"sites.":[23],"The":[24],"task":[25],"is":[26,87,142],"extremely":[27],"challenging":[28,179],"because":[29],"user":[31,96],"photos":[32,97],"(i.e.,":[33],"queries":[35],"this":[37],"scenario)":[38],"are":[39,52,105,194],"often":[40],"captured":[41],"uncontrolled":[43],"environments,":[44],"while":[45],"images":[48],"shops":[51],"mostly":[53],"taken":[54],"by":[55],"professionals":[56],"with":[57,76,201],"clean":[58],"backgrounds":[59],"and":[60,73,98,189],"perfect":[61],"lighting":[62],"conditions.":[63],"To":[64],"tackle":[65],"problem,":[67],"we":[68,108,127],"study":[69],"deep":[70,83,120],"network":[71],"architectures":[72],"training":[74,158],"schemes,":[75],"goal":[78],"learning":[80],"robust":[82,123,186],"feature":[84,148],"representation":[85],"that":[86,183],"able":[88],"bridge":[90],"domain":[92],"gap":[93],"between":[94],"images.":[102],"Our":[103],"contributions":[104],"two-fold.":[106],"First,":[107],"propose":[109],"an":[110],"alternative":[111],"popular":[114],"contrastive":[115,124,187],"loss":[116,188],"used":[117],"siamese":[119],"networks,":[121],"namely":[122],"loss,":[125],"where":[126],"\"relax\"":[128],"penalty":[130],"positive":[132],"pairs":[133],"alleviate":[135],"over-fitting.":[136],"Second,":[137],"multi-task":[139,191],"fine-tuning":[140,174,192],"approach":[141,193],"introduced":[143],"learn":[145],"better":[147],"representation,":[149],"which":[150],"not":[151],"only":[152],"incorporates":[153],"knowledge":[154],"from":[155,166],"provided":[157],"pairs,":[160],"but":[161],"also":[162],"explores":[163],"additional":[164],"information":[165],"large":[168],"ImageNet":[169],"dataset":[170],"regularize":[172],"procedure.":[175],"Experiments":[176],"two":[178],"datasets":[181],"demonstrate":[182],"both":[184],"effective,":[195],"leading":[196],"promising":[199],"results":[200],"time":[203],"cost":[204],"suitable":[205],"for":[206],"real-time":[207],"retrieval.":[208]},"counts_by_year":[{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":15},{"year":2017,"cited_by_count":9}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
