{"id":"https://openalex.org/W4393928604","doi":"https://doi.org/10.48550/arxiv.2404.01587","title":"TSCM: A Teacher-Student Model for Vision Place Recognition Using Cross-Metric Knowledge Distillation","display_name":"TSCM: A Teacher-Student Model for Vision Place Recognition Using Cross-Metric Knowledge Distillation","publication_year":2024,"publication_date":"2024-04-02","ids":{"openalex":"https://openalex.org/W4393928604","doi":"https://doi.org/10.48550/arxiv.2404.01587"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2404.01587","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2404.01587","pdf_url":"https://arxiv.org/pdf/2404.01587","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2404.01587","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032269741","display_name":"Yehui Shen","orcid":"https://orcid.org/0009-0000-9991-9524"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Shen, Yehui","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017613188","display_name":"Mingmin Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Mingmin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019035804","display_name":"Huimin Lu","orcid":"https://orcid.org/0000-0001-9794-3221"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Huimin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5032262344","display_name":"Xieyuanli Chen","orcid":"https://orcid.org/0000-0003-0955-6681"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Xieyuanli","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5032269741"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9965999722480774,"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"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9965999722480774,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9943000078201294,"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9569000005722046,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/metric","display_name":"Metric (unit)","score":0.725134551525116},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.7091505527496338},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4760296642780304},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44604623317718506},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35992687940597534},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3507629334926605},{"id":"https://openalex.org/keywords/mathematics-education","display_name":"Mathematics education","score":0.32677769660949707},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.24302363395690918},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1930508017539978},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.16400432586669922},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.13466238975524902},{"id":"https://openalex.org/keywords/operations-management","display_name":"Operations management","score":0.13420474529266357}],"concepts":[{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.725134551525116},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.7091505527496338},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4760296642780304},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44604623317718506},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35992687940597534},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3507629334926605},{"id":"https://openalex.org/C145420912","wikidata":"https://www.wikidata.org/wiki/Q853077","display_name":"Mathematics education","level":1,"score":0.32677769660949707},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.24302363395690918},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1930508017539978},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.16400432586669922},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.13466238975524902},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.13420474529266357}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2404.01587","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2404.01587","pdf_url":"https://arxiv.org/pdf/2404.01587","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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"},{"id":"doi:10.48550/arxiv.2404.01587","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2404.01587","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2404.01587","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2404.01587","pdf_url":"https://arxiv.org/pdf/2404.01587","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":[{"id":"https://openalex.org/G1812073829","display_name":null,"funder_award_id":"U191320","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2544253145","display_name":null,"funder_award_id":"U1913202","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3114819178","display_name":null,"funder_award_id":"2023QNRC001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G31562090","display_name":null,"funder_award_id":"62203460","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3408348127","display_name":null,"funder_award_id":"U22A2059","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5571399874","display_name":"Construction of a  Research Laboratory in Engineering Mechanics;","funder_award_id":"6220346","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6624834013","display_name":null,"funder_award_id":"U20A2019","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8400801390","display_name":null,"funder_award_id":"U20A201","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8544294156","display_name":null,"funder_award_id":"U20A20197","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8714109953","display_name":null,"funder_award_id":"QNRC001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4393928604.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3026162553","https://openalex.org/W2768175398","https://openalex.org/W2344382886","https://openalex.org/W19111321","https://openalex.org/W2412887479","https://openalex.org/W32245304","https://openalex.org/W2953684491","https://openalex.org/W4285338581","https://openalex.org/W2015158429","https://openalex.org/W3016498020"],"abstract_inverted_index":{"Visual":[0],"place":[1],"recognition":[2,131],"(VPR)":[3],"plays":[4],"a":[5,68],"pivotal":[6],"role":[7],"in":[8,128],"autonomous":[9],"exploration":[10],"and":[11,22,31,34,44,71,93,115,133],"navigation":[12],"of":[13,60,122,130,153],"mobile":[14],"robots":[15],"within":[16],"complex":[17],"outdoor":[18],"environments.":[19],"While":[20],"cost-effective":[21],"easily":[23],"deployed,":[24],"camera":[25],"sensors":[26],"are":[27],"sensitive":[28],"to":[29,57,85],"lighting":[30],"weather":[32],"changes,":[33],"even":[35],"slight":[36],"image":[37],"alterations":[38],"can":[39],"greatly":[40],"affect":[41],"VPR":[42],"efficiency":[43],"precision.":[45],"Existing":[46],"methods":[47],"overcome":[48],"this":[49,64],"by":[50],"exploiting":[51],"powerful":[52],"yet":[53],"large":[54],"networks,":[55],"leading":[56],"significant":[58],"consumption":[59],"computational":[61,102],"resources.":[62],"In":[63],"paper,":[65],"we":[66],"propose":[67],"high-performance":[69],"teacher":[70,92],"lightweight":[72],"student":[73,94],"distillation":[74,84,146],"framework":[75],"called":[76],"TSCM.":[77],"It":[78],"exploits":[79],"our":[80,123,138,154],"devised":[81],"cross-metric":[82],"knowledge":[83,145],"narrow":[86],"the":[87,91,120,143],"performance":[88,98],"gap":[89],"between":[90],"models,":[95],"maintaining":[96],"superior":[97],"while":[99],"enabling":[100],"minimal":[101],"load":[103],"during":[104],"deployment.":[105],"We":[106],"conduct":[107],"comprehensive":[108],"evaluations":[109],"on":[110],"large-scale":[111],"datasets,":[112],"namely":[113],"Pittsburgh30k":[114],"Pittsburgh250k.":[116],"Experimental":[117],"results":[118],"demonstrate":[119],"superiority":[121],"method":[124,155],"over":[125],"baseline":[126],"models":[127],"terms":[129],"accuracy":[132],"model":[134],"parameter":[135],"efficiency.":[136],"Moreover,":[137],"ablation":[139],"studies":[140],"show":[141],"that":[142],"proposed":[144],"technique":[147],"surpasses":[148],"other":[149],"counterparts.":[150],"The":[151],"code":[152],"has":[156],"been":[157],"released":[158],"at":[159],"https://github.com/nubot-nudt/TSCM.":[160]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
