{"id":"https://openalex.org/W4308234021","doi":"https://doi.org/10.1109/icip46576.2022.9897234","title":"Learning from Designers: Fashion Compatibility Analysis Via Dataset Distillation","display_name":"Learning from Designers: Fashion Compatibility Analysis Via Dataset Distillation","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4308234021","doi":"https://doi.org/10.1109/icip46576.2022.9897234"},"language":"en","primary_location":{"id":"doi:10.1109/icip46576.2022.9897234","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip46576.2022.9897234","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Image Processing (ICIP)","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/A5100599590","display_name":"Yulan Chen","orcid":"https://orcid.org/0000-0003-3567-2563"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yulan Chen","raw_affiliation_strings":["Tsinghua University,Beijing National Research Center for Information Science and Technology,Department of Computer Science and Technology","Department of Computer Science and Technology, Beijing National Research Center for Information Science and Technology, Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Beijing National Research Center for Information Science and Technology,Department of Computer Science and Technology","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Computer Science and Technology, Beijing National Research Center for Information Science and Technology, Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102869280","display_name":"Zhiyong Wu","orcid":"https://orcid.org/0000-0001-8533-0524"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyong Wu","raw_affiliation_strings":["Tsinghua University,Beijing National Research Center for Information Science and Technology,Department of Computer Science and Technology","Department of Computer Science and Technology, Beijing National Research Center for Information Science and Technology, Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Beijing National Research Center for Information Science and Technology,Department of Computer Science and Technology","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Computer Science and Technology, Beijing National Research Center for Information Science and Technology, Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112662608","display_name":"Zheyan Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheyan Shen","raw_affiliation_strings":["Tsinghua University,Beijing National Research Center for Information Science and Technology,Department of Computer Science and Technology","Department of Computer Science and Technology, Beijing National Research Center for Information Science and Technology, Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Beijing National Research Center for Information Science and Technology,Department of Computer Science and Technology","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Computer Science and Technology, Beijing National Research Center for Information Science and Technology, Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100405577","display_name":"Jia Jia","orcid":"https://orcid.org/0000-0003-3164-8988"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jia Jia","raw_affiliation_strings":["Tsinghua University,Beijing National Research Center for Information Science and Technology,Department of Computer Science and Technology","Department of Computer Science and Technology, Beijing National Research Center for Information Science and Technology, Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Beijing National Research Center for Information Science and Technology,Department of Computer Science and Technology","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Computer Science and Technology, Beijing National Research Center for Information Science and Technology, Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.3698,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.67932662,"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":"856","last_page":"860"},"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":0.996399998664856,"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":0.996399998664856,"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":0.9811999797821045,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9552000164985657,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/compatibility","display_name":"Compatibility (geochemistry)","score":0.8095521330833435},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7491182088851929},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6052534580230713},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.452729195356369},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4462786018848419},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4434100091457367},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1209568977355957}],"concepts":[{"id":"https://openalex.org/C2778648169","wikidata":"https://www.wikidata.org/wiki/Q967768","display_name":"Compatibility (geochemistry)","level":2,"score":0.8095521330833435},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7491182088851929},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6052534580230713},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.452729195356369},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4462786018848419},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4434100091457367},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1209568977355957},{"id":"https://openalex.org/C42360764","wikidata":"https://www.wikidata.org/wiki/Q83588","display_name":"Chemical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip46576.2022.9897234","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip46576.2022.9897234","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1821462560","https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2605066040","https://openalex.org/W2737102415","https://openalex.org/W2767109396","https://openalex.org/W2905373637","https://openalex.org/W2912727434","https://openalex.org/W2963258075","https://openalex.org/W2964015378","https://openalex.org/W2994996749","https://openalex.org/W3009183760","https://openalex.org/W3099462466","https://openalex.org/W3104731853","https://openalex.org/W3155403969","https://openalex.org/W3206068051","https://openalex.org/W6638523607","https://openalex.org/W6726873649","https://openalex.org/W6756054015","https://openalex.org/W6771685740"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Learning":[0],"fashion":[1,116,137],"compatibility":[2,126,153],"is":[3],"of":[4,61,143,159],"great":[5],"significance":[6],"to":[7,55,93],"both":[8],"academic":[9],"research":[10],"and":[11,27,48,58,122],"industry,":[12],"which":[13,112,155],"serves":[14],"as":[15,98],"a":[16,68,99],"key":[17],"technique":[18],"for":[19,44,118],"many":[20],"real":[21,135],"applications":[22],"like":[23],"online":[24],"shopping":[25],"recommendation":[26],"clothing":[28],"generation.":[29],"In":[30,80],"previous":[31],"studies,":[32],"user-generated":[33],"data":[34,97],"(e.g.":[35,77],"outfits":[36],"from":[37,115,162],"social":[38],"media":[39],"platform)":[40],"are":[41],"usually":[42],"used":[43],"learning":[45,121],"item":[46],"embeddings":[47],"further":[49],"modeling":[50,102],"the":[51,56,74,95,103,124,141,157],"compatibility.":[52,105],"However,":[53],"due":[54],"noisy":[57],"messy":[59],"nature":[60],"such":[62],"data,":[63],"one":[64],"can":[65,71],"hardly":[66],"learn":[67],"representation":[69,120],"that":[70],"clearly":[72,139],"characterize":[73],"fashion-related":[75],"attributes":[76],"color,":[78],"material).":[79],"this":[81],"paper,":[82],"we":[83,107],"propose":[84],"an":[85],"Attention-based":[86],"Dataset":[87],"Distillation":[88],"Graph":[89],"Neural":[90],"Network":[91],"(ADD-GNN)":[92],"leverage":[94],"designer-generated":[96],"guidance":[100],"on":[101,134],"outfit":[104,152],"Specifically,":[106],"jointly":[108],"optimize":[109],"two":[110],"components":[111],"distill":[113],"knowledge":[114,161],"designers":[117],"feature":[119],"model":[123],"overall":[125],"through":[127],"attention-based":[128],"graph":[129],"neural":[130],"network.":[131],"Experimental":[132],"results":[133],"world":[136],"datasets":[138],"demonstrate":[140],"superiority":[142],"our":[144],"proposed":[145],"ADD-GNN":[146],"against":[147],"several":[148],"competitive":[149],"baselines":[150],"in":[151],"tasks,":[154],"proves":[156],"effectiveness":[158],"distilling":[160],"designers.":[163]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
