{"id":"https://openalex.org/W7154958040","doi":"https://doi.org/10.48550/arxiv.2604.15631","title":"Causal Bootstrapped Alignment for Unsupervised Video-Based Visible-Infrared Person Re-Identification","display_name":"Causal Bootstrapped Alignment for Unsupervised Video-Based Visible-Infrared Person Re-Identification","publication_year":2026,"publication_date":"2026-04-17","ids":{"openalex":"https://openalex.org/W7154958040","doi":"https://doi.org/10.48550/arxiv.2604.15631"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.15631","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.15631","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.2604.15631","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134083041","display_name":"Shuang Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Shuang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134057547","display_name":"Jiaxu Leng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Leng, Jiaxu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116045201","display_name":"Changjiang Kuang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kuang, Changjiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056104115","display_name":"Mingpi Tan","orcid":"https://orcid.org/0000-0003-1952-6267"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tan, Mingpi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134059934","display_name":"Yu Yuan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuan, Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134052318","display_name":"Xinbo Gao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Xinbo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":[],"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.954800009727478,"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":0.954800009727478,"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":0.011500000022351742,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.009399999864399433,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/spurious-relationship","display_name":"Spurious relationship","score":0.6366000175476074},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6308000087738037},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.6118999719619751},{"id":"https://openalex.org/keywords/causal-consistency","display_name":"Causal consistency","score":0.5554999709129333},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.5200999975204468},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4632999897003174},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.44130000472068787},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.41600000858306885},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.39809998869895935},{"id":"https://openalex.org/keywords/bootstrapping","display_name":"Bootstrapping (finance)","score":0.3619000017642975}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7045999765396118},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.6366000175476074},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6308000087738037},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.6118999719619751},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5910000205039978},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5896000266075134},{"id":"https://openalex.org/C175652121","wikidata":"https://www.wikidata.org/wiki/Q4379351","display_name":"Causal consistency","level":5,"score":0.5554999709129333},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.5200999975204468},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4632999897003174},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.44130000472068787},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.41600000858306885},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.39809998869895935},{"id":"https://openalex.org/C207609745","wikidata":"https://www.wikidata.org/wiki/Q4944086","display_name":"Bootstrapping (finance)","level":2,"score":0.3619000017642975},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.35100001096725464},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.349700003862381},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.34599998593330383},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.3398999869823456},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.33809998631477356},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2906999886035919},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.28949999809265137},{"id":"https://openalex.org/C2779127903","wikidata":"https://www.wikidata.org/wiki/Q6510194","display_name":"Learning rule","level":3,"score":0.28630000352859497},{"id":"https://openalex.org/C37279795","wikidata":"https://www.wikidata.org/wiki/Q2492305","display_name":"Consistency model","level":3,"score":0.2854999899864197},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2818000018596649},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.28060001134872437},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.2745000123977661},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2676999866962433},{"id":"https://openalex.org/C163504300","wikidata":"https://www.wikidata.org/wiki/Q2364925","display_name":"Causal structure","level":2,"score":0.26750001311302185},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2671000063419342},{"id":"https://openalex.org/C31388003","wikidata":"https://www.wikidata.org/wiki/Q7624548","display_name":"Strong consistency","level":3,"score":0.2669999897480011},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.2669000029563904},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.26570001244544983},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.265500009059906},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.26339998841285706},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.26260000467300415},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.2549999952316284}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.15631","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.15631","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.2604.15631","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.15631","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":[{"id":"https://metadata.un.org/sdg/10","score":0.7385954260826111,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"VVI-ReID":[0,41],"is":[1],"a":[2,112,171],"critical":[3],"technique":[4],"for":[5,40,159],"all-day":[6],"surveillance,":[7],"where":[8],"temporal":[9,138],"information":[10],"provides":[11],"additional":[12],"cues":[13],"beyond":[14],"static":[15],"images.":[16],"However,":[17],"existing":[18,207],"approaches":[19],"rely":[20],"heavily":[21],"on":[22,196],"fully":[23],"supervised":[24],"learning":[25],"with":[26,60,191],"expensive":[27],"cross-modality":[28,104,142,177],"annotations,":[29],"limiting":[30],"scalability.":[31],"To":[32,106],"address":[33,107],"this":[34,58],"issue,":[35],"we":[36,110,125,163],"investigate":[37],"Unsupervised":[38],"Learning":[39],"(USL-VVI-ReID),":[42],"which":[43,131,169],"learns":[44],"identity-discriminative":[45],"representations":[46,158,183],"directly":[47],"from":[48,71],"unlabeled":[49],"video":[50,122],"tracklets.":[51],"Directly":[52],"extending":[53],"image-based":[54],"USL-VI-ReID":[55,208],"methods":[56,209],"to":[57,65,145,175,212],"setting":[59],"generic":[61],"pretrained":[62],"encoders":[63,69],"leads":[64],"suboptimal":[66],"performance.":[67],"Such":[68],"suffer":[70],"weak":[72],"identity":[73,83,139,143],"discrimination":[74],"and":[75,85,92,101,141,148,199],"strong":[76],"modality":[77],"bias,":[78],"resulting":[79],"in":[80],"severe":[81],"intra-modality":[82],"confusion":[84],"pronounced":[86],"clustering":[87],"granularity":[88,178],"imbalance":[89],"between":[90],"visible":[91,189],"infrared":[93,182],"modalities.":[94],"These":[95],"issues":[96],"jointly":[97],"degrade":[98],"pseudo-label":[99],"reliability":[100],"hinder":[102],"effective":[103],"alignment.":[105],"these":[108],"challenges,":[109],"propose":[111,164],"Causal":[113,127],"Bootstrapped":[114],"Alignment":[115],"(CBA)":[116],"framework":[117],"that":[118,203],"explicitly":[119],"exploits":[120],"inherent":[121],"priors.":[123],"First,":[124],"introduce":[126],"Intervention":[128],"Warm-up":[129],"(CIW),":[130],"performs":[132],"sequence-level":[133],"causal":[134],"interventions":[135],"by":[136],"leveraging":[137],"consistency":[140,144],"suppress":[146],"modality-":[147],"motion-induced":[149],"spurious":[150],"correlations":[151],"while":[152],"preserving":[153],"identity-relevant":[154],"semantics,":[155],"yielding":[156],"cleaner":[157],"unsupervised":[160],"clustering.":[161],"Second,":[162],"Prototype-Guided":[165],"Uncertainty":[166],"Refinement":[167],"(PGUR),":[168],"employs":[170],"coarse-to-fine":[172],"alignment":[173],"strategy":[174],"resolve":[176],"mismatch,":[179],"reorganizing":[180],"under-clustered":[181],"under":[184],"the":[185,197,213],"guidance":[186],"of":[187],"reliable":[188],"prototypes":[190],"uncertainty-aware":[192],"supervision.":[193],"Extensive":[194],"experiments":[195],"HITSZ-VCM":[198],"BUPTCampus":[200],"benchmarks":[201],"demonstrate":[202],"CBA":[204],"significantly":[205],"outperforms":[206],"when":[210],"extended":[211],"USL-VVI-ReID":[214],"setting.":[215]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-21T00:00:00"}