{"id":"https://openalex.org/W3035307345","doi":"https://doi.org/10.1109/icme46284.2020.9102974","title":"ABP: Adaptive Body Partition Model For Visible Infrared Person Re-Identification","display_name":"ABP: Adaptive Body Partition Model For Visible Infrared Person Re-Identification","publication_year":2020,"publication_date":"2020-06-09","ids":{"openalex":"https://openalex.org/W3035307345","doi":"https://doi.org/10.1109/icme46284.2020.9102974","mag":"3035307345"},"language":"en","primary_location":{"id":"doi:10.1109/icme46284.2020.9102974","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme46284.2020.9102974","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Multimedia and Expo (ICME)","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/A5112749527","display_name":"Ziyu Wei","orcid":"https://orcid.org/0000-0002-3094-3857"},"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":"Ziyu Wei","raw_affiliation_strings":["State Key Laboratory of Integrated Services Networks, School of Telecommunications Engineering, Xidian University, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Integrated Services Networks, School of Telecommunications Engineering, Xidian University, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011324535","display_name":"Xi Yang","orcid":"https://orcid.org/0000-0002-5791-3674"},"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":"Xi Yang","raw_affiliation_strings":["State Key Laboratory of Integrated Services Networks, School of Telecommunications Engineering, Xidian University, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Integrated Services Networks, School of Telecommunications Engineering, Xidian University, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042507268","display_name":"Nannan Wang","orcid":"https://orcid.org/0000-0002-4695-6134"},"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":["State Key Laboratory of Integrated Services Networks, School of Telecommunications Engineering, Xidian University, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Integrated Services Networks, School of Telecommunications Engineering, Xidian University, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035560190","display_name":"Bin Song","orcid":"https://orcid.org/0000-0002-8096-3370"},"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":"Bin Song","raw_affiliation_strings":["State Key Laboratory of Integrated Services Networks, School of Telecommunications Engineering, Xidian University, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Integrated Services Networks, School of Telecommunications Engineering, Xidian University, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","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":["State Key Laboratory of Integrated Services Networks, School of Electronic Engineering, Xidian University, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Integrated Services Networks, School of Electronic Engineering, Xidian University, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5112749527"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":1.2701,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.82338509,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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":0.994700014591217,"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":0.9901000261306763,"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":0.7893629670143127},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7527209520339966},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.736809492111206},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.7149196863174438},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6929330229759216},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6199405789375305},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5650402307510376},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5011730194091797},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.4988546371459961},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.49812865257263184},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4498507082462311},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43348631262779236},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.4299916625022888},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06607517600059509}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7893629670143127},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7527209520339966},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.736809492111206},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.7149196863174438},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6929330229759216},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6199405789375305},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5650402307510376},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5011730194091797},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.4988546371459961},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49812865257263184},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4498507082462311},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43348631262779236},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4299916625022888},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06607517600059509},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme46284.2020.9102974","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme46284.2020.9102974","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7400000095367432,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1949591461","https://openalex.org/W2161160262","https://openalex.org/W2220271458","https://openalex.org/W2596603442","https://openalex.org/W2777534232","https://openalex.org/W2788846526","https://openalex.org/W2808134123","https://openalex.org/W2808260522","https://openalex.org/W2904949947","https://openalex.org/W2954773727","https://openalex.org/W2963637710","https://openalex.org/W2963842104","https://openalex.org/W2964707258","https://openalex.org/W6747428963"],"related_works":["https://openalex.org/W1496222301","https://openalex.org/W3207760230","https://openalex.org/W1590307681","https://openalex.org/W4312814274","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W2353836703","https://openalex.org/W41015297","https://openalex.org/W4280645561"],"abstract_inverted_index":{"Person":[0],"re-identification":[1],"(Re-ID)":[2],"aims":[3],"to":[4,44,68,85,96,119],"match":[5],"pedestrian":[6,17],"images":[7,22],"cross":[8],"multiple":[9],"cameras.":[10],"Most":[11],"Re-ID":[12,35,135],"studies":[13],"focus":[14],"on":[15,105,132],"visible":[16],"images,":[18],"without":[19],"considering":[20],"the":[21,28,32,51,121,126,138,141,146],"obtained":[23],"by":[24],"infrared":[25],"cameras":[26],"in":[27],"dark.":[29],"To":[30],"solve":[31],"cross-modality":[33,127,134],"person":[34],"problem,":[36],"current":[37],"methods":[38],"usually":[39],"exploit":[40],"global":[41],"feature":[42,122],"descriptors":[43],"obtain":[45],"discriminative":[46],"representations.":[47,75],"However,":[48],"they":[49],"ignore":[50],"fine-grained":[52],"information":[53],"of":[54,77,140],"heterogeneous":[55],"images.":[56],"In":[57],"this":[58],"paper,":[59],"we":[60,89],"propose":[61],"an":[62,92],"adaptive":[63],"body":[64],"partition":[65],"(ABP)":[66],"model":[67],"automatically":[69],"detect":[70],"and":[71,102,113,124],"distinguish":[72],"effective":[73],"part":[74,111],"Instead":[76],"utilizing":[78],"a":[79,106],"two-stream":[80],"convolutional":[81],"neural":[82],"network":[83],"(CNN)":[84],"extract":[86],"modality-specific":[87],"information,":[88],"directly":[90],"design":[91],"end-to-end":[93],"one-stream":[94],"CNN":[95],"simultaneously":[97],"learn":[98],"multi-modality":[99],"sharable":[100],"features":[101],"map":[103],"them":[104],"common":[107],"space.":[108],"Global":[109],"loss,":[110],"losses":[112],"threefold":[114],"triplet":[115],"loss":[116],"are":[117],"integrated":[118],"enhance":[120],"discriminability":[123],"minimize":[125],"gap.":[128],"Extensive":[129],"experimental":[130],"results":[131],"two":[133],"datasets":[136],"exhibit":[137],"superiority":[139],"proposed":[142],"method":[143],"compared":[144],"with":[145],"state-of-the-art":[147],"solutions.":[148]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}