{"id":"https://openalex.org/W4391327741","doi":"https://doi.org/10.1109/vcip59821.2023.10402726","title":"Feature Decomposition and Attribute Augmentation for Attribute-based Person Search","display_name":"Feature Decomposition and Attribute Augmentation for Attribute-based Person Search","publication_year":2023,"publication_date":"2023-12-04","ids":{"openalex":"https://openalex.org/W4391327741","doi":"https://doi.org/10.1109/vcip59821.2023.10402726"},"language":"en","primary_location":{"id":"doi:10.1109/vcip59821.2023.10402726","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/vcip59821.2023.10402726","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Visual Communications and Image Processing (VCIP)","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/A5102949527","display_name":"Xin Wang","orcid":"https://orcid.org/0009-0006-6463-4338"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xin Wang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing,China","Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100386527","display_name":"Fangfang Liu","orcid":"https://orcid.org/0000-0003-2888-9860"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fangfang Liu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing,China","Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058648594","display_name":"Caili Guo","orcid":"https://orcid.org/0000-0001-8892-4520"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Caili Guo","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing,China","Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100415053","display_name":"Zheng Li","orcid":"https://orcid.org/0000-0003-2535-2523"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Li","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing,China","Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100396780","display_name":"Hao Zhang","orcid":"https://orcid.org/0009-0006-9207-9300"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Zhang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing,China","Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5102949527"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19517012,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9997000098228455,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9997000098228455,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9764999747276306,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9699000120162964,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.70844566822052},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.684269368648529},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6216862201690674},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5432097315788269},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5044690370559692},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40738728642463684}],"concepts":[{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.70844566822052},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.684269368648529},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6216862201690674},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5432097315788269},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5044690370559692},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40738728642463684},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vcip59821.2023.10402726","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/vcip59821.2023.10402726","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6000000238418579,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W2018006179","https://openalex.org/W2102497689","https://openalex.org/W2111025459","https://openalex.org/W2194775991","https://openalex.org/W2410968923","https://openalex.org/W2471048925","https://openalex.org/W2584637367","https://openalex.org/W2586899202","https://openalex.org/W2604463754","https://openalex.org/W2755066373","https://openalex.org/W2896632102","https://openalex.org/W2962996864","https://openalex.org/W2963040148","https://openalex.org/W2963289251","https://openalex.org/W2963365374","https://openalex.org/W2963506340","https://openalex.org/W2963805953","https://openalex.org/W2963842104","https://openalex.org/W2963882743","https://openalex.org/W2964044605","https://openalex.org/W2964260687","https://openalex.org/W2964304299","https://openalex.org/W2981393440","https://openalex.org/W2988695542","https://openalex.org/W2988964414","https://openalex.org/W3095440956","https://openalex.org/W3110337799","https://openalex.org/W3128205973","https://openalex.org/W3187261085","https://openalex.org/W3190140211","https://openalex.org/W4295754656","https://openalex.org/W4312533058","https://openalex.org/W4312998013","https://openalex.org/W4313013512","https://openalex.org/W4319299990","https://openalex.org/W4367663386","https://openalex.org/W4386065462"],"related_works":["https://openalex.org/W2380059383","https://openalex.org/W2063679720","https://openalex.org/W3147584709","https://openalex.org/W2075046161","https://openalex.org/W2185495545","https://openalex.org/W2547083368","https://openalex.org/W2031856784","https://openalex.org/W2977677679","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"The":[0],"attribute-based":[1],"person":[2],"search":[3],"task":[4],"aims":[5],"to":[6,33,45,59,89],"find":[7],"matching":[8],"pedestrian":[9],"images":[10],"by":[11,95],"text":[12],"attributes,":[13],"which":[14,41],"is":[15,23,53,128],"relevant":[16],"in":[17,66,71],"scenarios":[18],"where":[19],"no":[20],"query":[21],"image":[22,102],"given.":[24],"However,":[25],"the":[26,60,67,91,97,101,106,117,121,134,142,146,151,159],"existing":[27],"methods":[28],"exhibit":[29],"inferior":[30],"performance":[31],"due":[32,58],"their":[34,43],"inadequate":[35],"representation":[36],"of":[37,63,100,120,136,145,161],"local":[38,107],"fine-grained":[39],"features,":[40],"hinders":[42],"ability":[44,119,144],"effectively":[46,115,132],"model":[47],"intra-class":[48],"variations.":[49],"In":[50,75],"addition,":[51],"there":[52],"a":[54,80],"zero-shot":[55],"retrieval":[56],"problem":[57],"large":[61],"number":[62],"unseen":[64],"categories":[65],"test":[68],"set,":[69],"resulting":[70],"suboptimal":[72],"generalization":[73,143],"performance.":[74],"this":[76],"paper,":[77],"we":[78],"propose":[79],"novel":[81],"Feature":[82],"Decomposition":[83],"and":[84,140,155],"Attribute":[85],"Augmentation":[86],"(FDAA)":[87],"framework":[88],"solve":[90],"above":[92],"problems.":[93],"Firstly,":[94],"decomposing":[96],"global":[98],"features":[99,108],"from":[103],"different":[104],"directions,":[105],"are":[109],"extracted":[110],"at":[111],"multiple":[112],"granularities,":[113],"thus":[114],"improving":[116],"discrimination":[118],"model.":[122,147],"Secondly,":[123],"an":[124],"attribute":[125],"augmentation":[126],"strategy":[127],"proposed":[129,163],"that":[130],"can":[131],"expand":[133],"combination":[135],"attributes":[137],"during":[138],"training":[139],"improve":[141],"Extensive":[148],"experiments":[149],"on":[150],"PETA,":[152],"Market-1501":[153],"Attribute,":[154],"PA100K":[156],"datasets":[157],"demonstrate":[158],"effectiveness":[160],"our":[162],"method,":[164],"outperforming":[165],"state-of-the-art":[166],"methods.":[167]},"counts_by_year":[],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}