{"id":"https://openalex.org/W3047814667","doi":"https://doi.org/10.1145/3394171.3413689","title":"Hierarchical Bi-Directional Feature Perception Network for Person Re-Identification","display_name":"Hierarchical Bi-Directional Feature Perception Network for Person Re-Identification","publication_year":2020,"publication_date":"2020-10-12","ids":{"openalex":"https://openalex.org/W3047814667","doi":"https://doi.org/10.1145/3394171.3413689","mag":"3047814667"},"language":"en","primary_location":{"id":"doi:10.1145/3394171.3413689","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3413689","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":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2008.03509","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Zhipu Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhipu Liu","raw_affiliation_strings":["Chongqing University, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Lei Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Zhang","raw_affiliation_strings":["Chongqing University, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"last","author":{"id":null,"display_name":"Yang Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Yang","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9397,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.82822017,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"4289","last_page":"4298"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9958000183105469,"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":0.9901000261306763,"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/discriminative-model","display_name":"Discriminative model","score":0.7874000072479248},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.7678999900817871},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6323999762535095},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5178999900817871},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.49059998989105225},{"id":"https://openalex.org/keywords/bilinear-interpolation","display_name":"Bilinear interpolation","score":0.48330000042915344},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.3628999888896942}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7874000072479248},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7678999900817871},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7383000254631042},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7361000180244446},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6323999762535095},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5178999900817871},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.49059998989105225},{"id":"https://openalex.org/C205203396","wikidata":"https://www.wikidata.org/wiki/Q612143","display_name":"Bilinear interpolation","level":2,"score":0.48330000042915344},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.3628999888896942},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.33730000257492065},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.32850000262260437},{"id":"https://openalex.org/C101814296","wikidata":"https://www.wikidata.org/wiki/Q5439685","display_name":"Feature model","level":3,"score":0.3084000051021576},{"id":"https://openalex.org/C144986985","wikidata":"https://www.wikidata.org/wiki/Q871236","display_name":"Hierarchical database model","level":2,"score":0.30790001153945923},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.29910001158714294},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.29510000348091125},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28780001401901245},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2574999928474426},{"id":"https://openalex.org/C104122410","wikidata":"https://www.wikidata.org/wiki/Q1416406","display_name":"Network model","level":2,"score":0.25360000133514404}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3394171.3413689","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3413689","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:arXiv.org:2008.03509","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.03509","pdf_url":"https://arxiv.org/pdf/2008.03509","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2008.03509","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.03509","pdf_url":"https://arxiv.org/pdf/2008.03509","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1982925187","https://openalex.org/W2108598243","https://openalex.org/W2120419212","https://openalex.org/W2183341477","https://openalex.org/W2204750386","https://openalex.org/W2295107390","https://openalex.org/W2584637367","https://openalex.org/W2724213014","https://openalex.org/W2798775284","https://openalex.org/W2888159112","https://openalex.org/W2962691289","https://openalex.org/W2962706983","https://openalex.org/W2962926870","https://openalex.org/W2963078173","https://openalex.org/W2963365374","https://openalex.org/W2963842104","https://openalex.org/W2964304299","https://openalex.org/W2979931389","https://openalex.org/W2981420411","https://openalex.org/W2984145721","https://openalex.org/W2987151592","https://openalex.org/W2989923292","https://openalex.org/W2990827756","https://openalex.org/W2996695408","https://openalex.org/W2997738728"],"related_works":[],"abstract_inverted_index":{"Previous":[0],"Person":[1],"Re-Identification":[2],"(Re-ID)":[3],"models":[4],"aim":[5],"to":[6,50,84,93,124,127,154],"focus":[7],"on":[8,73,160],"the":[9,59,74,86,118,161,175],"most":[10],"discriminative":[11],"region":[12,24],"of":[13,62,89,148],"an":[14],"image,":[15],"while":[16],"its":[17],"performance":[18],"may":[19],"be":[20,155],"compromised":[21],"when":[22],"that":[23,171],"is":[25,82],"missing":[26],"caused":[27],"by":[28],"camera":[29],"viewpoint":[30],"changes":[31],"or":[32],"occlusion.":[33],"To":[34],"solve":[35],"this":[36],"issue,":[37],"we":[38,104,135],"propose":[39,105,136],"a":[40,106,129,137],"novel":[41,107,138],"model":[42],"named":[43],"Hierarchical":[44],"Bi-directional":[45,77],"Feature":[46,78],"Perception":[47,79],"Network":[48],"(HBFP-Net)":[49],"correlate":[51],"multi-level":[52,113],"information":[53,98],"and":[54,92,96,116,121,168],"reinforce":[55],"each":[56],"other.":[57],"First,":[58],"correlation":[60,75],"maps":[61,153],"cross-level":[63],"feature-pairs":[64],"are":[65],"modeled":[66],"via":[67],"low-rank":[68],"bilinear":[69],"pooling.":[70],"Then,":[71],"based":[72],"maps,":[76],"(BFP)":[80],"module":[81],"employed":[83],"enrich":[85],"attention":[87],"regions":[88],"high-level":[90],"feature,":[91],"learn":[94],"abstract":[95],"specific":[97],"in":[99,151],"low-level":[100],"feature.":[101],"And":[102],"then,":[103],"end-to-end":[108],"hierarchical":[109],"network":[110],"which":[111,142],"integrates":[112],"augmented":[114,119],"features":[115,123],"inputs":[117],"low-":[120],"middle-level":[122],"following":[125],"layers":[126],"retrain":[128],"new":[130],"powerful":[131],"network.":[132],"What's":[133],"more,":[134],"trainable":[139],"generalized":[140],"pooling,":[141],"can":[143],"dynamically":[144],"select":[145],"any":[146],"value":[147],"all":[149],"locations":[150],"feature":[152],"activated.":[156],"Extensive":[157],"experiments":[158],"implemented":[159],"mainstream":[162],"evaluation":[163],"datasets":[164],"including":[165],"Market-1501,":[166],"CUHK03":[167],"DukeMTMC-ReID":[169],"show":[170],"our":[172],"method":[173],"outperforms":[174],"recent":[176],"SOTA":[177],"Re-ID":[178],"models.":[179]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2020-08-13T00:00:00"}