{"id":"https://openalex.org/W3175075852","doi":"https://doi.org/10.1109/lsp.2021.3091924","title":"Semantic-Guided Pixel Sampling for Cloth-Changing Person Re-Identification","display_name":"Semantic-Guided Pixel Sampling for Cloth-Changing Person Re-Identification","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3175075852","doi":"https://doi.org/10.1109/lsp.2021.3091924","mag":"3175075852"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2021.3091924","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2021.3091924","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2107.11522","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076167141","display_name":"Xiujun Shu","orcid":"https://orcid.org/0000-0002-5976-6022"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiujun Shu","raw_affiliation_strings":["Peng Cheng Laboratory, Peking University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Peng Cheng Laboratory, Peking University, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793","https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100447691","display_name":"Ge Li","orcid":"https://orcid.org/0000-0003-0140-0949"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ge Li","raw_affiliation_strings":["School of Electronic and Computer Engineering, Peking University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Computer Engineering, Peking University, Shenzhen, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100411426","display_name":"Xiao Wang","orcid":"https://orcid.org/0000-0001-6117-6745"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Wang","raw_affiliation_strings":["Peng Cheng Laboratory, Peking University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Peng Cheng Laboratory, Peking University, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793","https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086468636","display_name":"Weijian Ruan","orcid":"https://orcid.org/0000-0003-3710-8739"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weijian Ruan","raw_affiliation_strings":["Peng Cheng Laboratory, Peking University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Peng Cheng Laboratory, Peking University, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793","https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100393506","display_name":"Qi Tian","orcid":"https://orcid.org/0000-0002-7252-5047"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Tian","raw_affiliation_strings":["Huawei Cloud and AI, Huawei Technologies, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Huawei Cloud and AI, Huawei Technologies, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5076167141"],"corresponding_institution_ids":["https://openalex.org/I20231570","https://openalex.org/I4210136793"],"apc_list":null,"apc_paid":null,"fwci":5.9249,"has_fulltext":false,"cited_by_count":95,"citation_normalized_percentile":{"value":0.97277372,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"28","issue":null,"first_page":"1365","last_page":"1369"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9976999759674072,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9972000122070312,"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/computer-science","display_name":"Computer science","score":0.8203110694885254},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7479662895202637},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.730282187461853},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5825819373130798},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.571845531463623},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5667015314102173},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5574825406074524},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5422325134277344},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5303816199302673},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.518994927406311},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4590737819671631},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44938981533050537},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4362125098705292},{"id":"https://openalex.org/keywords/sketch","display_name":"Sketch","score":0.4315900504589081},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.4190523326396942},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.29988908767700195},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.07923060655593872}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8203110694885254},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7479662895202637},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.730282187461853},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5825819373130798},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.571845531463623},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5667015314102173},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5574825406074524},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5422325134277344},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5303816199302673},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.518994927406311},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4590737819671631},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44938981533050537},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4362125098705292},{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.4315900504589081},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.4190523326396942},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.29988908767700195},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.07923060655593872},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","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":2,"locations":[{"id":"doi:10.1109/lsp.2021.3091924","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2021.3091924","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2107.11522","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2107.11522","pdf_url":"https://arxiv.org/pdf/2107.11522","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2107.11522","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2107.11522","pdf_url":"https://arxiv.org/pdf/2107.11522","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2605140638","display_name":null,"funder_award_id":"2019M660209","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1973255633","https://openalex.org/W2117539524","https://openalex.org/W2173158975","https://openalex.org/W2194775991","https://openalex.org/W2295107390","https://openalex.org/W2499468060","https://openalex.org/W2520774990","https://openalex.org/W2584637367","https://openalex.org/W2795758732","https://openalex.org/W2799185441","https://openalex.org/W2912406707","https://openalex.org/W2938798597","https://openalex.org/W2947930228","https://openalex.org/W2962926870","https://openalex.org/W2963180826","https://openalex.org/W2963842104","https://openalex.org/W2963854019","https://openalex.org/W2963854696","https://openalex.org/W2967515867","https://openalex.org/W2970575838","https://openalex.org/W2981959899","https://openalex.org/W2994675267","https://openalex.org/W2998508940","https://openalex.org/W2998792609","https://openalex.org/W3024437012","https://openalex.org/W3034249268","https://openalex.org/W3035216422","https://openalex.org/W3035275216","https://openalex.org/W3035400973","https://openalex.org/W3049063470","https://openalex.org/W3100506510","https://openalex.org/W3115879670","https://openalex.org/W3125736290","https://openalex.org/W3155284007","https://openalex.org/W4287251614","https://openalex.org/W6747428963","https://openalex.org/W6767109091"],"related_works":["https://openalex.org/W2378994405","https://openalex.org/W2385974820","https://openalex.org/W2373478030","https://openalex.org/W2378679551","https://openalex.org/W3149739944","https://openalex.org/W2392363776","https://openalex.org/W2063051341","https://openalex.org/W2591066345","https://openalex.org/W1494563618","https://openalex.org/W2357022711"],"abstract_inverted_index":{"Cloth-changing":[0],"person":[1,75],"re-identification":[2],"(re-ID)":[3],"is":[4,21,59,157,197],"a":[5,67,137,192],"new":[6],"rising":[7],"research":[8],"topic":[9],"that":[10,162],"aims":[11],"at":[12,199],"retrieving":[13],"pedestrians":[14],"whose":[15],"clothes":[16,103,128,167],"are":[17,44,163],"changed.":[18],"This":[19,64],"task":[20,58],"quite":[22],"challenging":[23],"and":[24,51,104,149,168],"has":[25],"not":[26,45,80],"been":[27],"fully":[28],"studied":[29],"to":[30,49,56,60,85,91,140,145,159,165],"date.":[31],"Current":[32],"works":[33],"mainly":[34],"focus":[35],"on":[36,174,184],"body":[37],"shape":[38],"or":[39,129],"contour":[40],"sketch,":[41],"but":[42,87,123],"they":[43],"robust":[46],"enough":[47],"due":[48],"view":[50],"posture":[52],"variations.":[53],"The":[54,116,195],"key":[55],"this":[57,153],"exploit":[61],"cloth-irrelevant":[62,94],"cues.":[63,95],"paper":[65],"proposes":[66],"semantic-guided":[68],"pixel":[69],"sampling":[70,111],"approach":[71],"for":[72],"the":[73,89,100,120,125,142,155,175],"cloth-changing":[74],"re-ID":[76],"task.":[77],"We":[78,170],"do":[79],"explicitly":[81],"define":[82],"which":[83,187],"feature":[84],"extract":[86],"force":[88],"model":[90,156],"automatically":[92],"learn":[93,160],"Specifically,":[96],"we":[97,135],"firstly":[98],"recognize":[99],"pedestrian's":[101],"upper":[102,166],"pants,":[105],"then":[106],"randomly":[107],"change":[108],"them":[109],"by":[110],"pixels":[112,126],"from":[113],"other":[114],"pedestrians.":[115,133],"changed":[117],"samples":[118],"retain":[119],"identity":[121],"labels":[122],"exchange":[124],"of":[127],"pants":[130],"among":[131],"different":[132],"Besides,":[134],"adopt":[136],"loss":[138],"function":[139],"constrain":[141],"learned":[143],"features":[144],"keep":[146],"consistent":[147],"before":[148],"after":[150],"changes.":[151],"In":[152],"way,":[154],"forced":[158],"cues":[161],"irrelevant":[164],"pants.":[169],"conduct":[171],"extensive":[172],"experiments":[173],"latest":[176],"released":[177],"PRCC":[178],"dataset.":[179],"Our":[180],"method":[181],"achieved":[182],"65.8%":[183],"Rank1":[185],"accuracy,":[186],"outperforms":[188],"previous":[189],"methods":[190],"with":[191],"large":[193],"margin.":[194],"code":[196],"available":[198],"<uri":[200],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[201],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/shuxjweb/pixel_sampling.git</uri>":[202],".":[203]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":27},{"year":2024,"cited_by_count":24},{"year":2023,"cited_by_count":20},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-04T08:04:53.788161","created_date":"2025-10-10T00:00:00"}