{"id":"https://openalex.org/W2982170673","doi":"https://doi.org/10.1145/3343031.3351006","title":"Dual-alignment Feature Embedding for Cross-modality Person Re-identification","display_name":"Dual-alignment Feature Embedding for Cross-modality Person Re-identification","publication_year":2019,"publication_date":"2019-10-15","ids":{"openalex":"https://openalex.org/W2982170673","doi":"https://doi.org/10.1145/3343031.3351006","mag":"2982170673"},"language":"en","primary_location":{"id":"doi:10.1145/3343031.3351006","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3343031.3351006","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM International Conference on Multimedia","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/A5101603174","display_name":"Hao Yi","orcid":"https://orcid.org/0000-0003-2582-7939"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yi Hao","raw_affiliation_strings":["Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100690630","display_name":"Nannan Wang","orcid":"https://orcid.org/0000-0003-1435-489X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nannan Wang","raw_affiliation_strings":["Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101785348","display_name":"Xinbo Gao","orcid":"https://orcid.org/0000-0003-1443-0776"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinbo Gao","raw_affiliation_strings":["Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103271811","display_name":"Jie Li","orcid":"https://orcid.org/0000-0002-9769-8024"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Li","raw_affiliation_strings":["Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100357613","display_name":"Xiaoyu Wang","orcid":"https://orcid.org/0000-0002-6431-8822"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaoyu Wang","raw_affiliation_strings":["Intellifusion, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Intellifusion, Shenzhen, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101603174"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":4.7008,"has_fulltext":false,"cited_by_count":87,"citation_normalized_percentile":{"value":0.96009928,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"57","last_page":"65"},"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":0.9975000023841858,"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":0.9926000237464905,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7865455150604248},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.753827691078186},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.676213264465332},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.6669570207595825},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6326756477355957},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6118330359458923},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5764718651771545},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.49961113929748535},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.45495808124542236},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.45227062702178955},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4166610538959503},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21724116802215576}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7865455150604248},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.753827691078186},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.676213264465332},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.6669570207595825},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6326756477355957},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6118330359458923},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5764718651771545},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.49961113929748535},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45495808124542236},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.45227062702178955},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4166610538959503},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21724116802215576},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3343031.3351006","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3343031.3351006","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7300000190734863,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1516807289","https://openalex.org/W1949591461","https://openalex.org/W2044800651","https://openalex.org/W2194775991","https://openalex.org/W2220271458","https://openalex.org/W2353169560","https://openalex.org/W2586899202","https://openalex.org/W2596603442","https://openalex.org/W2724213014","https://openalex.org/W2795758732","https://openalex.org/W2896234850","https://openalex.org/W2904949947","https://openalex.org/W2962691289","https://openalex.org/W2962926870","https://openalex.org/W2963322158","https://openalex.org/W2963435138","https://openalex.org/W2963633722","https://openalex.org/W2963842104","https://openalex.org/W2963882743","https://openalex.org/W2963910742","https://openalex.org/W3016005719","https://openalex.org/W3100506510","https://openalex.org/W3100927979","https://openalex.org/W6688974507"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W2110523656","https://openalex.org/W1482209366","https://openalex.org/W2521627374"],"abstract_inverted_index":{"Person":[0],"re-identification":[1,24,47],"aims":[2],"at":[3],"searching":[4],"pedestrians":[5],"across":[6,104],"different":[7],"cameras,":[8],"which":[9,25],"is":[10,73],"a":[11,30,59],"key":[12],"problem":[13],"in":[14,19,38],"video":[15],"surveillance.":[16],"With":[17],"requirements":[18],"night":[20],"environment,":[21],"RGB-infrared":[22,45],"person":[23,46,123],"could":[26],"be":[27],"regarded":[28],"as":[29],"cross-modality":[31,43,122],"matching":[32],"problem,":[33],"has":[34],"gained":[35],"increasing":[36],"attention":[37],"recent":[39],"years.":[40],"Aside":[41],"from":[42,50],"discrepancy,":[44],"also":[48],"suffers":[49],"human":[51],"pose":[52],"and":[53,77,95,106,117,131,150],"view":[54],"point":[55],"differences.":[56],"We":[57,80,90,145],"design":[58],"dual-alignment":[60,72],"feature":[61],"embedding":[62,102],"method":[63],"to":[64,85,99],"extract":[65,86,112],"discriminative":[66],"modality-invariant":[67,113],"features.":[68],"The":[69],"concept":[70],"of":[71],"two":[74,141],"folds:":[75],"spatial":[76],"modality":[78],"alignments.":[79],"adopt":[81],"the":[82,101,128,137,154],"part-level":[83],"features":[84,103,114],"fine-grained":[87],"camera-invariant":[88],"information.":[89],"introduce":[91],"distribution":[92],"loss":[93,97],"function":[94,98],"correlation":[96],"align":[100],"visible":[105],"infrared":[107],"modalities.":[108],"Finally,":[109],"we":[110],"can":[111],"with":[115,136],"robust":[116],"rich":[118],"identity":[119],"embeddings":[120],"for":[121],"re-identification.":[124],"Experiment":[125],"confirms":[126],"that":[127],"proposed":[129],"baseline":[130],"improvement":[132],"achieves":[133],"competitive":[134],"results":[135],"state-of-the-art":[138],"methods":[139],"on":[140,153],"datasets.":[142],"For":[143],"instance,":[144],"achieve":[146],"(57.5+12.6)%":[147],"rank-1":[148],"accuracy":[149],"(57.3+11.8)%":[151],"mAP":[152],"RegDB":[155],"dataset.":[156]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":22},{"year":2022,"cited_by_count":17},{"year":2021,"cited_by_count":21},{"year":2020,"cited_by_count":8},{"year":2018,"cited_by_count":2}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}
