乐胖代购免代理版

{"id":"https://openalex.org/W2964346648","doi":"https://doi.org/10.1109/avss.2017.8078460","title":"Multi-Region bilinear convolutional neural networks for person re-identification","display_name":"Multi-Region bilinear convolutional neural networks for person re-identification","publication_year":2017,"publication_date":"2017-08-01","ids":{"openalex":"https://openalex.org/W2964346648","doi":"https://doi.org/10.1109/avss.2017.8078460","mag":"2964346648"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss.2017.8078460","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1512.05300","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5084873226","display_name":"Evgeniya Ustinova","orcid":null},"institutions":[{"id":"https://openalex.org/I125989756","display_name":"Skolkovo Institute of Science and Technology","ror":"https://ror.org/03f9nc143","country_code":"RU","type":"funder","lineage":["https://openalex.org/I125989756"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Evgeniya Ustinova","raw_affiliation_strings":["Skolkovo Institute of Science and Technology, Moscow"],"affiliations":[{"raw_affiliation_string":"Skolkovo Institute of Science and Technology, Moscow","institution_ids":["https://openalex.org/I125989756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011937456","display_name":"Yaroslav Ganin","orcid":null},"institutions":[{"id":"https://openalex.org/I125989756","display_name":"Skolkovo Institute of Science and Technology","ror":"https://ror.org/03f9nc143","country_code":"RU","type":"funder","lineage":["https://openalex.org/I125989756"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Yaroslav Ganin","raw_affiliation_strings":["Skolkovo Institute of Science and Technology, Moscow Montreal Institute for Learning Algorithms, Montreal, Quebec"],"affiliations":[{"raw_affiliation_string":"Skolkovo Institute of Science and Technology, Moscow Montreal Institute for Learning Algorithms, Montreal, Quebec","institution_ids":["https://openalex.org/I125989756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083458209","display_name":"Victor Lempitsky","orcid":"https://orcid.org/0000-0003-4118-710X"},"institutions":[{"id":"https://openalex.org/I125989756","display_name":"Skolkovo Institute of Science and Technology","ror":"https://ror.org/03f9nc143","country_code":"RU","type":"funder","lineage":["https://openalex.org/I125989756"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Victor Lempitsky","raw_affiliation_strings":["Skolkovo Institute of Science and Technology, Moscow"],"affiliations":[{"raw_affiliation_string":"Skolkovo Institute of Science and Technology, Moscow","institution_ids":["https://openalex.org/I125989756"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.633,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":162,"citation_normalized_percentile":{"value":0.925662,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":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/T12740","display_name":"Gait Recognition and Analysis","score":0.9982,"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"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9979,"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/pooling","display_name":"Pooling","score":0.8809689},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.63394356},{"id":"https://openalex.org/keywords/identification","display_name":"Identification","score":0.54790753}],"concepts":[{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.8809689},{"id":"https://openalex.org/C205203396","wikidata":"https://www.wikidata.org/wiki/Q612143","display_name":"Bilinear interpolation","level":2,"score":0.83980674},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.776526},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.77101564},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.63394356},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.630515},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.54790753},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.53748333},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5109948},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46780753},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.45657635},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4538972},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.42551643},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38020372},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.21838176},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09153661},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08027068},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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}],"mesh":[],"locations_count":2,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss.2017.8078460","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/1512.05300","pdf_url":"https://arxiv.org/pdf/1512.05300","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/1512.05300","pdf_url":"https://arxiv.org/pdf/1512.05300","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[{"score":0.82,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":32,"referenced_works":["https://openalex.org/W1142012885","https://openalex.org/W140822990","https://openalex.org/W1590195836","https://openalex.org/W1602182271","https://openalex.org/W1797268635","https://openalex.org/W1920259731","https://openalex.org/W1928419358","https://openalex.org/W1941498359","https://openalex.org/W1949591461","https://openalex.org/W1982925187","https://openalex.org/W2029287185","https://openalex.org/W2034883938","https://openalex.org/W2062677035","https://openalex.org/W2088830654","https://openalex.org/W2098807270","https://openalex.org/W2104657103","https://openalex.org/W2113609219","https://openalex.org/W2117060632","https://openalex.org/W2157364932","https://openalex.org/W2162915993","https://openalex.org/W2204750386","https://openalex.org/W2300840837","https://openalex.org/W2342611082","https://openalex.org/W2491664569","https://openalex.org/W2502225121","https://openalex.org/W2547446130","https://openalex.org/W2952335662","https://openalex.org/W3099224353","https://openalex.org/W3100555577","https://openalex.org/W3102668440","https://openalex.org/W4295700283","https://openalex.org/W4298190105"],"related_works":["https://openalex.org/W4380083739","https://openalex.org/W4285020665","https://openalex.org/W4280638452","https://openalex.org/W3160506688","https://openalex.org/W3111811104","https://openalex.org/W2963066927","https://openalex.org/W2950524887","https://openalex.org/W2883502031","https://openalex.org/W2810679507","https://openalex.org/W2261271299"],"abstract_inverted_index":{"In":[0],"this":[1],"work":[2],"we":[3,69],"propose":[4],"a":[5,72,83,93,100,111],"new":[6,128,152],"architecture":[7,27,57,97,129,153],"for":[8,42],"person":[9],"re-identification.":[10],"As":[11],"the":[12,31,50,54,60,123,127,131,155,174,178,185],"task":[13],"of":[14,45,53,126,169,177,187],"re-identification":[15],"is":[16,28,90],"inherently":[17],"associated":[18],"with":[19],"embedding":[20,74],"learning":[21],"and":[22,106,109,116,173],"non-rigid":[23,47],"appearance":[24],"description,":[25],"our":[26],"based":[29],"on":[30,130,157,166],"deep":[32],"bilinear":[33,80,107],"convolutional":[34,104],"network":[35],"(Bilinear-CNN)":[36],"that":[37,71,143],"has":[38],"been":[39],"proposed":[40],"recently":[41],"fine-grained":[43],"classification":[44],"highly":[46],"objects.":[48],"While":[49],"last":[51],"stages":[52],"original":[55],"Bilinear-CNN":[56,145],"completely":[58,117],"removes":[59],"geometric":[61],"information":[62],"from":[63],"consideration":[64],"by":[65,78],"performing":[66,79,162],"orderless":[67],"pooling,":[68],"observe":[70],"better":[73,163],"can":[75],"be":[76,181],"learned":[77],"pooling":[81,89],"in":[82],"more":[84],"local":[85],"way,":[86],"where":[87],"each":[88],"confined":[91],"to":[92,141],"predefined":[94],"region.":[95],"Our":[96],"thus":[98],"represents":[99],"compromise":[101],"between":[102,113],"traditional":[103],"networks":[105],"CNNs":[108],"strikes":[110],"balance":[112],"rigid":[114],"matching":[115],"ignoring":[118],"spatial":[119],"information.":[120],"We":[121],"perform":[122],"experimental":[124],"validation":[125],"three":[132,159],"popular":[133],"benchmark":[134],"datasets":[135],"(Market-1501,":[136],"CUHK01,":[137],"CUHK03),":[138],"comparing":[139],"it":[140],"baselines":[142],"include":[144],"as":[146,148],"well":[147],"prior":[149],"art.":[150],"The":[151,171],"outperforms":[154],"baseline":[156],"all":[158],"datasets,":[160],"while":[161],"than":[164],"state-of-the-art":[165],"two":[167],"out":[168],"three.":[170],"code":[172],"pretrained":[175],"models":[176],"approach":[179],"will":[180],"made":[182],"available":[183],"at":[184],"time":[186],"publication.":[188]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2964346648","counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":19},{"year":2019,"cited_by_count":58},{"year":2018,"cited_by_count":37},{"year":2017,"cited_by_count":13},{"year":2016,"cited_by_count":2}],"updated_date":"2025-02-17T22:17:01.949142","created_date":"2019-07-30"}