{"id":"https://openalex.org/W4312317456","doi":"https://doi.org/10.1109/tim.2022.3219466","title":"Salient-VPR: Salient Weighted Global Descriptor for Visual Place Recognition","display_name":"Salient-VPR: Salient Weighted Global Descriptor for Visual Place Recognition","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312317456","doi":"https://doi.org/10.1109/tim.2022.3219466"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2022.3219466","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3219466","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-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/A5100628775","display_name":"Ke Wang","orcid":"https://orcid.org/0000-0002-0797-4655"},"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":"Ke Wang","raw_affiliation_strings":["College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-0797-4655","affiliations":[{"raw_affiliation_string":"College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008124888","display_name":"Shengjie Luo","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":"Shengjie Luo","raw_affiliation_strings":["College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0003-1770-4592","affiliations":[{"raw_affiliation_string":"College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033708755","display_name":"Tao Chen","orcid":"https://orcid.org/0000-0001-9690-3340"},"institutions":[{"id":"https://openalex.org/I4210131649","display_name":"China Automotive Engineering Research Institute","ror":"https://ror.org/039jhgf83","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210131649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Chen","raw_affiliation_strings":["China Automotive Engineering Research Institute Company Ltd., Chongqing, China","China Automotive Engineering Research Institute Company, Ltd, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0001-9690-3340","affiliations":[{"raw_affiliation_string":"China Automotive Engineering Research Institute Company Ltd., Chongqing, China","institution_ids":["https://openalex.org/I4210131649"]},{"raw_affiliation_string":"China Automotive Engineering Research Institute Company, Ltd, Chongqing, China","institution_ids":["https://openalex.org/I4210131649"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021950355","display_name":"Jianbo L\u01da","orcid":"https://orcid.org/0000-0001-9088-5663"},"institutions":[{"id":"https://openalex.org/I1292974536","display_name":"Ford Motor Company (United States)","ror":"https://ror.org/00g2tkw06","country_code":"US","type":"company","lineage":["https://openalex.org/I1292974536"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianbo Lu","raw_affiliation_strings":["Research and Advanced Engineering, Ford Motor Company, Dearborn, MI, USA"],"raw_orcid":"https://orcid.org/0000-0001-9088-5663","affiliations":[{"raw_affiliation_string":"Research and Advanced Engineering, Ford Motor Company, Dearborn, MI, USA","institution_ids":["https://openalex.org/I1292974536"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":null,"fwci":1.2429,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.79751187,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":"71","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998999834060669,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998999834060669,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.996999979019165,"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/salient","display_name":"Salient","score":0.8658807277679443},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7303687334060669},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7288135290145874},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6333982944488525},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5879870057106018},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.5431053638458252},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4918093979358673},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.4518047869205475},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.44025468826293945},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.4230685532093048},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3940650224685669},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.342357873916626}],"concepts":[{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.8658807277679443},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7303687334060669},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7288135290145874},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6333982944488525},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5879870057106018},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.5431053638458252},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4918093979358673},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.4518047869205475},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.44025468826293945},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.4230685532093048},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3940650224685669},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.342357873916626},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2022.3219466","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3219466","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","id":"https://metadata.un.org/sdg/13","score":0.4699999988079071}],"awards":[{"id":"https://openalex.org/G3878248778","display_name":null,"funder_award_id":"51605054","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":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1994729382","https://openalex.org/W2012592962","https://openalex.org/W2284029970","https://openalex.org/W2340897893","https://openalex.org/W2499468060","https://openalex.org/W2560609797","https://openalex.org/W2619522967","https://openalex.org/W2620629206","https://openalex.org/W2706729717","https://openalex.org/W2810077221","https://openalex.org/W2828529635","https://openalex.org/W2897085414","https://openalex.org/W2910281775","https://openalex.org/W2916040547","https://openalex.org/W2951019013","https://openalex.org/W2963588253","https://openalex.org/W2963708168","https://openalex.org/W2981381717","https://openalex.org/W2990519439","https://openalex.org/W3045438908","https://openalex.org/W3048054706","https://openalex.org/W3083208433","https://openalex.org/W3104616167","https://openalex.org/W3173736705","https://openalex.org/W3198130126","https://openalex.org/W3204429916","https://openalex.org/W3206622090","https://openalex.org/W4207027252","https://openalex.org/W4312854990","https://openalex.org/W4313039600","https://openalex.org/W6739520758","https://openalex.org/W6758454295"],"related_works":["https://openalex.org/W2607572884","https://openalex.org/W2536452361","https://openalex.org/W3195820617","https://openalex.org/W2328068029","https://openalex.org/W2100100476","https://openalex.org/W3186305498","https://openalex.org/W2726222394","https://openalex.org/W2040854736","https://openalex.org/W2165406585","https://openalex.org/W2744160734"],"abstract_inverted_index":{"Visual":[0],"place":[1],"recognition":[2,168],"(VPR)":[3],"is":[4],"a":[5,58,124,133,171],"widely":[6],"investigated":[7],"but":[8],"challenging":[9,174],"problem,":[10],"which":[11,136],"must":[12],"deal":[13],"with":[14],"the":[15,63,77,82,111,138,141,149],"twin":[16],"problems":[17],"of":[18,113,140,151,173],"changed":[19],"appearance":[20],"caused":[21,147],"by":[22,43,148],"varying":[23],"weather":[24],"conditions,":[25],"illumination,":[26],"and":[27,49,143,153,180],"seasons,":[28],"as":[29,31,177],"well":[30],"dynamic":[32],"objects":[33,115],"in":[34,81,162],"complex":[35],"environments.":[36],"In":[37],"this":[38],"paper,":[39],"we":[40,87,104,131],"proposed":[41],"Salient-VPR":[42],"combining":[44,62],"image":[45,85],"retrieval,":[46],"semantic":[47,65,91,96,101,152],"information,":[48],"saliency":[50,107,154],"cues":[51],"to":[52,98,109],"achieve":[53],"accurate":[54],"estimations.":[55],"We":[56],"provides":[57],"novel":[59],"formulation":[60],"for":[61,127],"local":[64,90],"features":[66],"into":[67],"global":[68,72,100,160],"descriptors.":[69,102],"Unlike":[70],"traditional":[71,159],"descriptors":[73,92,108,161],"that":[74],"typically":[75],"summarize":[76],"whole":[78],"visual":[79,166],"content":[80],"images":[83],"or":[84],"regions,":[86],"aggregate":[88],"dense":[89],"based":[93],"on":[94,170],"pixel-level":[95],"scores":[97,169],"form":[99],"Then":[103],"calculate":[105],"predicted":[106],"learn":[110],"representation":[112],"static":[114],"from":[116,123],"images.":[117],"These":[118],"salient":[119],"descriptions":[120],"are":[121],"learned":[122],"dataset":[125],"tailored":[126],"VPR":[128],"missions.":[129],"Lastly,":[130],"introduce":[132],"late-fusion":[134],"module,":[135],"increases":[137],"stability":[139],"descriptor":[142],"avoids":[144],"performance":[145],"degradation":[146],"limitations":[150],"prediction.":[155],"Our":[156],"method":[157],"outperforms":[158],"experiments,":[163],"attaining":[164],"state-of-the-art":[165],"location":[167],"variety":[172],"datasets":[175],"such":[176],"Pitts30k,":[178],"MSLS,":[179],"Tokyo24/7.":[181]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":2}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}