{"id":"https://openalex.org/W4306833676","doi":"https://doi.org/10.1109/tip.2022.3207024","title":"Sampling Agnostic Feature Representation for Long-Term Person Re-Identification","display_name":"Sampling Agnostic Feature Representation for Long-Term Person Re-Identification","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4306833676","doi":"https://doi.org/10.1109/tip.2022.3207024","pmid":"https://pubmed.ncbi.nlm.nih.gov/36256692"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2022.3207024","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2022.3207024","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5080676914","display_name":"Seongyeop Yang","orcid":"https://orcid.org/0000-0001-7996-3990"},"institutions":[{"id":"https://openalex.org/I118373667","display_name":"Seoul National University of Science and Technology","ror":"https://ror.org/00chfja07","country_code":"KR","type":"education","lineage":["https://openalex.org/I118373667"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seongyeop Yang","raw_affiliation_strings":["Department of Electrical and Information Engineering, Seoul National University of Science and Technology, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0001-7996-3990","affiliations":[{"raw_affiliation_string":"Department of Electrical and Information Engineering, Seoul National University of Science and Technology, Seoul, South Korea","institution_ids":["https://openalex.org/I118373667"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032328702","display_name":"Byeongkeun Kang","orcid":"https://orcid.org/0000-0003-2537-7720"},"institutions":[{"id":"https://openalex.org/I118373667","display_name":"Seoul National University of Science and Technology","ror":"https://ror.org/00chfja07","country_code":"KR","type":"education","lineage":["https://openalex.org/I118373667"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Byeongkeun Kang","raw_affiliation_strings":["Department of Electronic Engineering, Seoul National University of Science and Technology, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-2537-7720","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Seoul National University of Science and Technology, Seoul, South Korea","institution_ids":["https://openalex.org/I118373667"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004957625","display_name":"Yeejin Lee","orcid":"https://orcid.org/0000-0002-3439-5042"},"institutions":[{"id":"https://openalex.org/I118373667","display_name":"Seoul National University of Science and Technology","ror":"https://ror.org/00chfja07","country_code":"KR","type":"education","lineage":["https://openalex.org/I118373667"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yeejin Lee","raw_affiliation_strings":["Department of Electrical and Information Engineering, Seoul National University of Science and Technology, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-3439-5042","affiliations":[{"raw_affiliation_string":"Department of Electrical and Information Engineering, Seoul National University of Science and Technology, Seoul, South Korea","institution_ids":["https://openalex.org/I118373667"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I118373667"],"apc_list":null,"apc_paid":null,"fwci":2.4366,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.90471592,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"31","issue":null,"first_page":"6412","last_page":"6423"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":1.0,"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":1.0,"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":0.9955999851226807,"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":0.9919000267982483,"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":0.7179452180862427},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6881019473075867},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6840165257453918},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6458284854888916},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6232725381851196},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5833479762077332},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5832603573799133},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5680508017539978},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5513906478881836},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.5179454684257507},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.4826934337615967},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4409370422363281},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4166381061077118},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.364324688911438},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.12020844221115112}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7179452180862427},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6881019473075867},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6840165257453918},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6458284854888916},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6232725381851196},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5833479762077332},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5832603573799133},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5680508017539978},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5513906478881836},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.5179454684257507},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.4826934337615967},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4409370422363281},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4166381061077118},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.364324688911438},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.12020844221115112},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","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},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D056667","descriptor_name":"Biometric Identification","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D056667","descriptor_name":"Biometric Identification","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D056667","descriptor_name":"Biometric Identification","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2022.3207024","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2022.3207024","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:36256692","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36256692","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7300000190734863}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":61,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1951304353","https://openalex.org/W1982925187","https://openalex.org/W2096733369","https://openalex.org/W2187089797","https://openalex.org/W2204750386","https://openalex.org/W2295107390","https://openalex.org/W2467139031","https://openalex.org/W2531440880","https://openalex.org/W2584637367","https://openalex.org/W2598634450","https://openalex.org/W2736410039","https://openalex.org/W2770739811","https://openalex.org/W2795758732","https://openalex.org/W2883348239","https://openalex.org/W2895526696","https://openalex.org/W2911605057","https://openalex.org/W2962691289","https://openalex.org/W2962706983","https://openalex.org/W2962770929","https://openalex.org/W2962926870","https://openalex.org/W2963049565","https://openalex.org/W2963350250","https://openalex.org/W2963446712","https://openalex.org/W2963690547","https://openalex.org/W2963703618","https://openalex.org/W2963775347","https://openalex.org/W2963842104","https://openalex.org/W2963854696","https://openalex.org/W2963901085","https://openalex.org/W2966961956","https://openalex.org/W2967515867","https://openalex.org/W2978794003","https://openalex.org/W2978968642","https://openalex.org/W2980791334","https://openalex.org/W2991736044","https://openalex.org/W2994675267","https://openalex.org/W2998792609","https://openalex.org/W3034249268","https://openalex.org/W3034303554","https://openalex.org/W3034727830","https://openalex.org/W3034903425","https://openalex.org/W3035070480","https://openalex.org/W3035275216","https://openalex.org/W3100506510","https://openalex.org/W3112897560","https://openalex.org/W3119699484","https://openalex.org/W3125736290","https://openalex.org/W3176695237","https://openalex.org/W3186064588","https://openalex.org/W3186928351","https://openalex.org/W3189128863","https://openalex.org/W3202132355","https://openalex.org/W3214294103","https://openalex.org/W4287251614","https://openalex.org/W6631190155","https://openalex.org/W6728374919","https://openalex.org/W6735531217","https://openalex.org/W6743446608","https://openalex.org/W6746316091","https://openalex.org/W6794524072"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W1557094818","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W4246352526","https://openalex.org/W2121910908","https://openalex.org/W915438175"],"abstract_inverted_index":{"Person":[0],"re-identification":[1,19],"is":[2,22,110,157],"a":[3,24,82,120,123],"problem":[4,26],"of":[5,31,40,52,57,63,73,115],"identifying":[6],"individuals":[7],"across":[8],"non-overlapping":[9],"cameras.":[10],"Although":[11],"remarkable":[12],"progress":[13],"has":[14],"been":[15],"made":[16],"in":[17,139],"the":[18,32,47,61,69,74,116,125,134,154],"problem,":[20],"it":[21],"still":[23],"challenging":[25],"due":[27],"to":[28,112],"appearance":[29],"variations":[30],"same":[33,117],"person":[34,118],"as":[35,37,119],"well":[36],"other":[38,143],"people":[39],"similar":[41],"appearance.":[42],"Some":[43],"prior":[44,161],"works":[45],"solved":[46],"issues":[48],"by":[49],"separating":[50],"features":[51,56],"positive":[53],"samples":[54,75,114],"from":[55,98,142],"negative":[58],"ones.":[59],"However,":[60],"performances":[62],"existing":[64],"models":[65],"considerably":[66],"depend":[67],"on":[68,148],"characteristics":[70],"and":[71],"statistics":[72],"used":[76],"for":[77],"training.":[78],"Thus,":[79],"we":[80],"propose":[81],"novel":[83],"framework":[84,127],"named":[85],"sampling":[86,105],"independent":[87,106],"robust":[88],"feature":[89,96],"representation":[90],"network":[91],"(SirNet)":[92],"that":[93,153],"learns":[94],"disentangled":[95],"embedding":[97],"randomly":[99],"chosen":[100],"samples.":[101],"A":[102],"carefully":[103],"designed":[104],"maximum":[107],"discrepancy":[108],"loss":[109],"introduced":[111],"model":[113,156],"cluster.":[121],"As":[122],"result,":[124],"proposed":[126,155],"can":[128],"generate":[129],"additional":[130],"hard":[131],"negatives/positives":[132],"using":[133],"learned":[135],"features,":[136],"which":[137],"results":[138,147],"better":[140],"discriminability":[141],"identities.":[144],"Extensive":[145],"experimental":[146],"large-scale":[149],"benchmark":[150],"datasets":[151],"verify":[152],"more":[158],"effective":[159],"than":[160],"state-of-the-art":[162],"models.":[163]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":7}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
