{"id":"https://openalex.org/W2967515867","doi":"https://doi.org/10.1109/cvprw.2019.00190","title":"Bag of Tricks and a Strong Baseline for Deep Person Re-Identification","display_name":"Bag of Tricks and a Strong Baseline for Deep Person Re-Identification","publication_year":2019,"publication_date":"2019-06-01","ids":{"openalex":"https://openalex.org/W2967515867","doi":"https://doi.org/10.1109/cvprw.2019.00190","mag":"2967515867"},"language":"en","primary_location":{"id":"doi:10.1109/cvprw.2019.00190","doi":"https://doi.org/10.1109/cvprw.2019.00190","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw.2019.00190","pdf_url":null,"source":{"id":"https://openalex.org/S4363607748","display_name":"IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1903.07071","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071538550","display_name":"Hao Luo","orcid":"https://orcid.org/0000-0002-6405-4011","observed_orcids":["https://orcid.org/0000-0002-6405-4011","https://orcid.org/0009-0004-7605-5638"]},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Luo","raw_affiliation_strings":["Zhejiang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064513874","display_name":"Youzhi Gu","orcid":"https://orcid.org/0000-0003-4619-2688","observed_orcids":["https://orcid.org/0000-0003-4619-2688"]},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youzhi Gu","raw_affiliation_strings":["Zhejiang University, Hangzhou, China","(Zhejiang University)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]},{"raw_affiliation_string":"(Zhejiang University)","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xingyu Liao","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingyu Liao","raw_affiliation_strings":["Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101685414","display_name":"Shenqi Lai","orcid":"https://orcid.org/0000-0001-8673-2218","observed_orcids":["https://orcid.org/0000-0001-8673-2218"]},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shenqi Lai","raw_affiliation_strings":["Xi'an Jiaotong University","Xi\u2019an Jiaotong University#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi'an Jiaotong University","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"Xi\u2019an Jiaotong University#TAB#","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002942261","display_name":"Wei Jiang","orcid":"https://orcid.org/0000-0002-9240-5851","observed_orcids":["https://orcid.org/0000-0002-9240-5851"]},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Jiang","raw_affiliation_strings":["Zhejiang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":56.2573,"has_fulltext":true,"cited_by_count":1614,"citation_normalized_percentile":{"value":0.99886126,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1487","last_page":"1495"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9945999979972839,"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":0.9945999979972839,"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":0.0010999999940395355,"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/T11448","display_name":"Face recognition and analysis","score":0.000699999975040555,"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/person-re-identification","display_name":"person re-identification","score":0.9980000257492065},{"id":"https://openalex.org/keywords/deep-neural-network","display_name":"deep neural network","score":0.8050000071525574},{"id":"https://openalex.org/keywords/global-features","display_name":"global features","score":0.800000011920929},{"id":"https://openalex.org/keywords/baseline-model","display_name":"baseline model","score":0.5770000219345093},{"id":"https://openalex.org/keywords/market-1501","display_name":"Market-1501","score":0.7770000100135803}],"concepts":[{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.9005367755889893},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7842345237731934},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6541830897331238},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.577369213104248},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5433124303817749},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5279257297515869},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4655260443687439},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4175407290458679},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38760906457901},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06147781014442444},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"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/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":3,"locations":[{"id":"doi:10.1109/cvprw.2019.00190","doi":"https://doi.org/10.1109/cvprw.2019.00190","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw.2019.00190","pdf_url":null,"source":{"id":"https://openalex.org/S4363607748","display_name":"IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1903.07071","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1903.07071","pdf_url":"https://arxiv.org/pdf/1903.07071","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,"listed_in":[],"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"},{"id":"doi:10.48550/arxiv.1903.07071","doi":"https://doi.org/10.48550/arxiv.1903.07071","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1903.07071","pdf_url":null,"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,"listed_in":[],"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1903.07071","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1903.07071","pdf_url":"https://arxiv.org/pdf/1903.07071","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,"listed_in":[],"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":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G3856905517","display_name":null,"funder_award_id":"61633019","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2967515867.pdf","grobid_xml":"https://content.openalex.org/works/W2967515867.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W1677182931","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2204750386","https://openalex.org/W2511791013","https://openalex.org/W2520774990","https://openalex.org/W2584637367","https://openalex.org/W2598634450","https://openalex.org/W2755066373","https://openalex.org/W2769346661","https://openalex.org/W2769925982","https://openalex.org/W2794497862","https://openalex.org/W2796364723","https://openalex.org/W2797394071","https://openalex.org/W2810967842","https://openalex.org/W2895786668","https://openalex.org/W2896888563","https://openalex.org/W2898047322","https://openalex.org/W2898083898","https://openalex.org/W2901862901","https://openalex.org/W2962926870","https://openalex.org/W2963637710","https://openalex.org/W2963842104","https://openalex.org/W2964044605","https://openalex.org/W2964130064","https://openalex.org/W2964186374","https://openalex.org/W2979931389","https://openalex.org/W2984040540","https://openalex.org/W2998508940","https://openalex.org/W3098711604"],"related_works":["https://openalex.org/W2996695408","https://openalex.org/W2986308140","https://openalex.org/W3203805178","https://openalex.org/W4297910398","https://openalex.org/W3009224839","https://openalex.org/W3215619737","https://openalex.org/W2944780724","https://openalex.org/W2783702274","https://openalex.org/W3045732585","https://openalex.org/W4206389681"],"abstract_inverted_index":{"This":[0,57],"paper":[1,58],"explores":[2],"a":[3],"simple":[4],"and":[5,22,37,61,80,92],"efficient":[6],"baseline":[7],"for":[8],"person":[9,68],"re-identification":[10,13],"(ReID).":[11],"Person":[12],"(ReID)":[14],"with":[15,85],"deep":[16],"neural":[17],"networks":[18],"has":[19],"made":[20],"progress":[21],"achieved":[23],"high":[24],"performance":[25],"in":[26,51,67],"recent":[27],"years.":[28],"However,":[29],"many":[30],"state-of-the-arts":[31],"methods":[32],"design":[33],"complex":[34],"network":[35],"structure":[36],"concatenate":[38],"multi-branch":[39],"features.":[40,89],"In":[41],"the":[42,75],"literature,":[43],"some":[44],"effective":[45,64],"training":[46,65],"tricks":[47,66,73],"are":[48,94],"briefly":[49],"appeared":[50],"several":[52],"papers":[53],"or":[54],"source":[55],"codes.":[56],"will":[59],"collect":[60],"evaluate":[62],"these":[63,72],"ReID.":[69],"By":[70],"combining":[71],"together,":[74],"model":[76],"achieves":[77],"94.5%":[78],"rank-1":[79],"85.9%":[81],"mAP":[82],"on":[83],"Market1501":[84],"only":[86],"using":[87],"global":[88],"Our":[90],"codes":[91],"models":[93],"available":[95],"at":[96],"https://github.com/michuanhaohao/reid-strong-baseline.":[97]},"counts_by_year":[{"year":2026,"cited_by_count":162},{"year":2025,"cited_by_count":248},{"year":2024,"cited_by_count":256},{"year":2023,"cited_by_count":251},{"year":2022,"cited_by_count":252},{"year":2021,"cited_by_count":263},{"year":2020,"cited_by_count":147},{"year":2019,"cited_by_count":34},{"year":2016,"cited_by_count":1}],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2019-08-22T00:00:00"}
