{"id":"https://openalex.org/W7127900181","doi":"https://doi.org/10.1007/978-981-95-5758-5_13","title":"Pose Guided Cross-Modal Invariant Feature Learning for\u00a0Visible-Infrared Person Re-identification","display_name":"Pose Guided Cross-Modal Invariant Feature Learning for\u00a0Visible-Infrared Person Re-identification","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7127900181","doi":"https://doi.org/10.1007/978-981-95-5758-5_13"},"language":"en","primary_location":{"id":"doi:10.1007/978-981-95-5758-5_13","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-981-95-5758-5_13","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","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/A5125137004","display_name":"Sheng Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sheng Zhang","raw_affiliation_strings":["College of Computer Science and Technology, Qingdao University, Qingdao, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Qingdao University, Qingdao, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110616728","display_name":"T. L. Teng","orcid":"https://orcid.org/0009-0001-3107-6118"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"TongJiaHao Teng","raw_affiliation_strings":["College of Computer Science and Technology, Qingdao University, Qingdao, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Qingdao University, Qingdao, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5125193611","display_name":"XiaoWei Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"XiaoWei Zhang","raw_affiliation_strings":["College of Computer Science and Technology, Qingdao University, Qingdao, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Qingdao University, Qingdao, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5125193611"],"corresponding_institution_ids":[],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.72204848,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"160","last_page":"174"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.82669997215271,"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":0.82669997215271,"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":0.05290000140666962,"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":0.031300000846385956,"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/cosine-similarity","display_name":"Cosine similarity","score":0.6158999800682068},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6122000217437744},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.5910999774932861},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.5860999822616577},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.557699978351593},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.545799970626831},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.5164999961853027},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5138000249862671},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5019999742507935}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8418999910354614},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7343000173568726},{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.6158999800682068},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6122000217437744},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.5910999774932861},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.5860999822616577},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.557699978351593},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.545799970626831},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.5164999961853027},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5138000249862671},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5019999742507935},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49900001287460327},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4244999885559082},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4092999994754791},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.36959999799728394},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3675999939441681},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3578000068664551},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.34700000286102295},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.32510000467300415},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.2906999886035919},{"id":"https://openalex.org/C2982962833","wikidata":"https://www.wikidata.org/wiki/Q17092450","display_name":"Information fusion","level":2,"score":0.2888000011444092},{"id":"https://openalex.org/C97385483","wikidata":"https://www.wikidata.org/wiki/Q16954980","display_name":"Deep belief network","level":3,"score":0.2727999985218048},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.25380000472068787},{"id":"https://openalex.org/C143271835","wikidata":"https://www.wikidata.org/wiki/Q254515","display_name":"Similitude","level":2,"score":0.2515000104904175}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-981-95-5758-5_13","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-981-95-5758-5_13","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5480946898460388,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W2596603442","https://openalex.org/W2620998106","https://openalex.org/W2777534232","https://openalex.org/W2808260522","https://openalex.org/W2904949947","https://openalex.org/W2954773727","https://openalex.org/W2962858109","https://openalex.org/W2963588253","https://openalex.org/W2963842104","https://openalex.org/W2985033611","https://openalex.org/W2998792609","https://openalex.org/W3033235266","https://openalex.org/W3034519219","https://openalex.org/W3035241963","https://openalex.org/W3107848599","https://openalex.org/W3139438386","https://openalex.org/W3176633985","https://openalex.org/W3202788649","https://openalex.org/W3204075450","https://openalex.org/W3210946531","https://openalex.org/W4214736485","https://openalex.org/W4283792038","https://openalex.org/W4307974001","https://openalex.org/W4312594135","https://openalex.org/W4312622050","https://openalex.org/W4312700302","https://openalex.org/W4312936309","https://openalex.org/W4313188957","https://openalex.org/W4386065398","https://openalex.org/W4386066270","https://openalex.org/W4390872891","https://openalex.org/W4390874481","https://openalex.org/W4402753418","https://openalex.org/W4405717802","https://openalex.org/W4406857548"],"related_works":[],"abstract_inverted_index":null,"counts_by_year":[],"updated_date":"2026-02-07T23:10:03.332741","created_date":"2026-02-07T00:00:00"}