{"id":"https://openalex.org/W3092676209","doi":"https://doi.org/10.1145/3394171.3413673","title":"Dual Gaussian-based Variational Subspace Disentanglement for Visible-Infrared Person Re-Identification","display_name":"Dual Gaussian-based Variational Subspace Disentanglement for Visible-Infrared Person Re-Identification","publication_year":2020,"publication_date":"2020-10-12","ids":{"openalex":"https://openalex.org/W3092676209","doi":"https://doi.org/10.1145/3394171.3413673","mag":"3092676209"},"language":"en","primary_location":{"id":"doi:10.1145/3394171.3413673","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3413673","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/1887/3418406","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049953967","display_name":"Nan Pu","orcid":"https://orcid.org/0000-0002-2179-8301"},"institutions":[{"id":"https://openalex.org/I121797337","display_name":"Leiden University","ror":"https://ror.org/027bh9e22","country_code":"NL","type":"education","lineage":["https://openalex.org/I121797337"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Nan Pu","raw_affiliation_strings":["Leiden University, Leiden, Netherlands"],"affiliations":[{"raw_affiliation_string":"Leiden University, Leiden, Netherlands","institution_ids":["https://openalex.org/I121797337"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100740611","display_name":"Wei Chen","orcid":"https://orcid.org/0000-0002-9696-0641"},"institutions":[{"id":"https://openalex.org/I121797337","display_name":"Leiden University","ror":"https://ror.org/027bh9e22","country_code":"NL","type":"education","lineage":["https://openalex.org/I121797337"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Wei Chen","raw_affiliation_strings":["Leiden University, Leiden, Netherlands"],"affiliations":[{"raw_affiliation_string":"Leiden University, Leiden, Netherlands","institution_ids":["https://openalex.org/I121797337"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004895426","display_name":"Yu Liu","orcid":"https://orcid.org/0000-0002-2067-9175"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Yu Liu","raw_affiliation_strings":["KU Leuven, Leuven, Belgium"],"affiliations":[{"raw_affiliation_string":"KU Leuven, Leuven, Belgium","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047471651","display_name":"Erwin M. Bakker","orcid":"https://orcid.org/0000-0002-2624-5271"},"institutions":[{"id":"https://openalex.org/I121797337","display_name":"Leiden University","ror":"https://ror.org/027bh9e22","country_code":"NL","type":"education","lineage":["https://openalex.org/I121797337"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Erwin M. Bakker","raw_affiliation_strings":["Leiden University, Leiden, Netherlands"],"affiliations":[{"raw_affiliation_string":"Leiden University, Leiden, Netherlands","institution_ids":["https://openalex.org/I121797337"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107877141","display_name":"Michael S. Lew","orcid":null},"institutions":[{"id":"https://openalex.org/I121797337","display_name":"Leiden University","ror":"https://ror.org/027bh9e22","country_code":"NL","type":"education","lineage":["https://openalex.org/I121797337"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Michael S. Lew","raw_affiliation_strings":["Leiden University, Leuven, Netherlands"],"affiliations":[{"raw_affiliation_string":"Leiden University, Leuven, Netherlands","institution_ids":["https://openalex.org/I121797337"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5049953967"],"corresponding_institution_ids":["https://openalex.org/I121797337"],"apc_list":null,"apc_paid":null,"fwci":5.2015,"has_fulltext":false,"cited_by_count":91,"citation_normalized_percentile":{"value":0.96553211,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2149","last_page":"2158"},"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/T11019","display_name":"Image Enhancement Techniques","score":0.995199978351593,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9909999966621399,"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":0.7089382410049438},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6387254595756531},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.6295866966247559},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5357450842857361},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5306780934333801},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.4912497401237488},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.4722311496734619},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.45123204588890076},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.43644165992736816},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35985368490219116},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33078569173812866}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7089382410049438},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6387254595756531},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6295866966247559},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5357450842857361},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5306780934333801},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.4912497401237488},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.4722311496734619},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.45123204588890076},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.43644165992736816},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35985368490219116},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33078569173812866},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/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/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3394171.3413673","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3413673","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Multimedia","raw_type":"proceedings-article"},{"id":"pmh:oai:scholarlypublications.universiteitleiden.nl:item_3418406","is_oa":false,"landing_page_url":"https://hdl.handle.net/1887/3418406","pdf_url":null,"source":{"id":"https://openalex.org/S4306400850","display_name":"Leiden Repository (Leiden University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I121797337","host_organization_name":"Leiden University","host_organization_lineage":["https://openalex.org/I121797337"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"MM '20: proceedings of the 28th ACM international conference on multimedia","raw_type":"Article in monograph or in proceedings"},{"id":"pmh:ul:oai:scholarlypublications.universiteitleiden.nl:item_3418406","is_oa":true,"landing_page_url":"http://hdl.handle.net/1887/3418406","pdf_url":null,"source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"MM '20: proceedings of the 28th ACM international conference on multimedia, 2149 - 2158. New York, NY, U.S.A.: ACM","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:ul:oai:scholarlypublications.universiteitleiden.nl:item_3418406","is_oa":true,"landing_page_url":"http://hdl.handle.net/1887/3418406","pdf_url":null,"source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"MM '20: proceedings of the 28th ACM international conference on multimedia, 2149 - 2158. New York, NY, U.S.A.: ACM","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7200000286102295}],"awards":[{"id":"https://openalex.org/G1426318481","display_name":null,"funder_award_id":"grant","funder_id":"https://openalex.org/F4320322725","funder_display_name":"China Scholarship Council"},{"id":"https://openalex.org/G8589651859","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320322725","funder_display_name":"China Scholarship Council"}],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"},{"id":"https://openalex.org/F4320320929","display_name":"Universiteit Leiden","ror":"https://ror.org/027bh9e22"},{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1959608418","https://openalex.org/W2095705004","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2264380076","https://openalex.org/W2596603442","https://openalex.org/W2730106296","https://openalex.org/W2753738274","https://openalex.org/W2795758732","https://openalex.org/W2798874329","https://openalex.org/W2808134123","https://openalex.org/W2808260522","https://openalex.org/W2890159224","https://openalex.org/W2904949947","https://openalex.org/W2910135751","https://openalex.org/W2912406707","https://openalex.org/W2949007385","https://openalex.org/W2954773727","https://openalex.org/W2962793481","https://openalex.org/W2963010714","https://openalex.org/W2963049565","https://openalex.org/W2963073614","https://openalex.org/W2963667985","https://openalex.org/W2978968642","https://openalex.org/W2980850643","https://openalex.org/W2981396627","https://openalex.org/W2981420411","https://openalex.org/W2982170673","https://openalex.org/W2983640911","https://openalex.org/W2985033611","https://openalex.org/W2990155616","https://openalex.org/W2990827756","https://openalex.org/W2997877744","https://openalex.org/W3000723049","https://openalex.org/W3009238880","https://openalex.org/W3034519219","https://openalex.org/W3041399281","https://openalex.org/W3100506510","https://openalex.org/W3101862707","https://openalex.org/W3159890710","https://openalex.org/W4301409532","https://openalex.org/W6688974507"],"related_works":["https://openalex.org/W1980381208","https://openalex.org/W2364594919","https://openalex.org/W2167092671","https://openalex.org/W2385859805","https://openalex.org/W1861706286","https://openalex.org/W2530972254","https://openalex.org/W2219338811","https://openalex.org/W2149583853","https://openalex.org/W2151402979","https://openalex.org/W1578916557"],"abstract_inverted_index":{"Visible-infrared":[0],"person":[1,22],"re-identification":[2,23],"(VI-ReID)":[3],"is":[4],"a":[5,44,63,68,137],"challenging":[6],"and":[7,56,67],"essential":[8],"task":[9],"in":[10],"night-time":[11],"intelligent":[12],"surveillance":[13],"systems.":[14],"Except":[15],"for":[16,83,99],"the":[17,34,40,100,104,111,116,120,127,145],"intra-modality":[18],"variance":[19,31],"that":[20,115,152],"RGB-RGB":[21],"mainly":[24],"overcomes,":[25],"VI-ReID":[26,160],"suffers":[27],"from":[28],"additional":[29],"inter-modality":[30],"caused":[32],"by":[33],"inherent":[35],"heterogeneous":[36],"gap.":[37],"To":[38,85],"solve":[39],"problem,":[41],"we":[42,92,135],"present":[43],"carefully":[45],"designed":[46],"dual":[47],"Gaussian-based":[48],"variational":[49,96],"auto-encoder":[50],"(DG-VAE),":[51],"which":[52,107],"disentangles":[53],"an":[54,57],"identity-discriminable":[55,76,112],"identity-ambiguous":[58],"cross-modality":[59,75,121],"feature":[60],"subspace,":[61],"following":[62],"mixture-of-Gaussians":[64],"(MoG)":[65],"prior":[66,102],"standard":[69],"Gaussian":[70],"distribution":[71,129],"prior,":[72],"respectively.":[73],"Disentangling":[74],"features":[77],"leads":[78],"to":[79,130,143],"more":[80],"robust":[81],"retrieval":[82],"VI-ReID.":[84],"achieve":[86],"efficient":[87],"optimization":[88],"like":[89],"conventional":[90],"VAE,":[91],"theoretically":[93],"derive":[94],"two":[95,159],"inference":[97],"terms":[98],"MoG":[101,128],"under":[103],"supervised":[105],"setting,":[106],"not":[108],"only":[109],"restricts":[110],"subspace":[113],"so":[114],"model":[117],"explicitly":[118],"handles":[119],"intra-identity":[122],"variance,":[123],"but":[124],"also":[125],"enables":[126],"avoid":[131],"posterior":[132],"collapse.":[133],"Furthermore,":[134],"propose":[136],"triplet":[138],"swap":[139],"reconstruction":[140],"(TSR)":[141],"strategy":[142],"promote":[144],"above":[146],"disentangling":[147],"process.":[148],"Extensive":[149],"experiments":[150],"demonstrate":[151],"our":[153],"method":[154],"outperforms":[155],"state-of-the-art":[156],"methods":[157],"on":[158],"datasets.":[161],"Codes":[162],"will":[163],"be":[164],"available":[165],"at":[166],"https://github.com/TPCD/DG-VAE.":[167]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":22},{"year":2023,"cited_by_count":30},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":9}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}