{"id":"https://openalex.org/W7154141645","doi":"https://doi.org/10.48550/arxiv.2604.09249","title":"FashionStylist: An Expert Knowledge-enhanced Multimodal Dataset for Fashion Understanding","display_name":"FashionStylist: An Expert Knowledge-enhanced Multimodal Dataset for Fashion Understanding","publication_year":2026,"publication_date":"2026-04-10","ids":{"openalex":"https://openalex.org/W7154141645","doi":"https://doi.org/10.48550/arxiv.2604.09249"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.09249","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09249","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.09249","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133511064","display_name":"Kaidong Feng","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Feng, Kaidong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133533856","display_name":"Zhuoxuan Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Zhuoxuan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075613260","display_name":"Hai-Feng Guo","orcid":"https://orcid.org/0000-0002-7558-8465"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Huizhong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133537853","display_name":"Yuting Jin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jin, Yuting","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133502822","display_name":"Xinyu Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Xinyu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133492794","display_name":"Yue Liang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang, Yue","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040690864","display_name":"Yifei Gai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gai, Yifei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133508241","display_name":"Li Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Li","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133515442","display_name":"Yunshan Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Yunshan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133502811","display_name":"Zhu Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Zhu","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":10,"corresponding_author_ids":["https://openalex.org/A5133511064"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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":0.9437999725341797,"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":0.9437999725341797,"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":0.012299999594688416,"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"}},{"id":"https://openalex.org/T12514","display_name":"Fashion and Cultural Textiles","score":0.012199999764561653,"subfield":{"id":"https://openalex.org/subfields/1209","display_name":"Museology"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6559000015258789},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.5285000205039978},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.42739999294281006},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.4081999957561493},{"id":"https://openalex.org/keywords/cover","display_name":"Cover (algebra)","score":0.4025999903678894}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7175999879837036},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6559000015258789},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.5285000205039978},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.42739999294281006},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.41940000653266907},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4138999879360199},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.4081999957561493},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.4025999903678894},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3662000000476837},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.36320000886917114},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.31459999084472656},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.28700000047683716},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.25200000405311584},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.25099998712539673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.09249","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09249","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.09249","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09249","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Fashion":[0],"understanding":[1],"requires":[2],"both":[3,72],"visual":[4],"perception":[5],"and":[6,13,22,35,55,75,87,101,108,115,145],"expert-level":[7,56,109],"reasoning":[8],"about":[9],"style,":[10,112],"occasion,":[11,114],"compatibility,":[12],"outfit":[14,29,42,76,85,88],"rationale.":[15],"However,":[16],"existing":[17],"fashion":[18,57,132,151],"datasets":[19],"remain":[20],"fragmented":[21],"task-specific,":[23],"often":[24],"focusing":[25],"on":[26],"item":[27,74,94],"attributes,":[28],"co-occurrence,":[30],"or":[31],"weak":[32],"textual":[33],"supervision,":[34],"thus":[36],"provide":[37],"limited":[38],"support":[39],"for":[40,53,130,141],"holistic":[41,54],"understanding.":[43,58],"In":[44],"this":[45],"paper,":[46],"we":[47],"introduce":[48],"FashionStylist,":[49],"an":[50,137],"expert-annotated":[51],"benchmark":[52,129],"Constructed":[59],"through":[60],"a":[61,127],"dedicated":[62],"fashion-expert":[63],"annotation":[64],"pipeline,":[65],"FashionStylist":[66,122],"provides":[67],"professionally":[68],"grounded":[69],"annotations":[70],"at":[71],"the":[73],"levels.":[77],"It":[78],"supports":[79],"three":[80],"representative":[81],"tasks:":[82],"outfit-to-item":[83],"grounding,":[84,143],"completion,":[86,144],"evaluation.":[89],"These":[90],"tasks":[91],"cover":[92],"realistic":[93],"recovery":[95],"from":[96],"complex":[97],"outfits":[98],"with":[99],"layering":[100],"accessories,":[102],"compatibility-aware":[103],"composition":[104],"beyond":[105],"co-occurrence":[106],"matching,":[107],"assessment":[110],"of":[111],"season,":[113],"overall":[116],"coherence.":[117],"Experimental":[118],"results":[119],"show":[120],"that":[121],"serves":[123],"not":[124],"only":[125],"as":[126,136],"unified":[128],"multiple":[131],"tasks,":[133],"but":[134],"also":[135],"effective":[138],"training":[139],"resource":[140],"improving":[142],"outfit-level":[146],"semantic":[147],"evaluation":[148],"in":[149],"MLLM-based":[150],"systems.":[152]},"counts_by_year":[],"updated_date":"2026-04-14T06:08:25.285971","created_date":"2026-04-14T00:00:00"}
