{"id":"https://openalex.org/W4385079919","doi":"https://doi.org/10.1109/iscas46773.2023.10181441","title":"Neighborhood Learning from Noisy Labels for Cross-Modal Retrieval","display_name":"Neighborhood Learning from Noisy Labels for Cross-Modal Retrieval","publication_year":2023,"publication_date":"2023-05-21","ids":{"openalex":"https://openalex.org/W4385079919","doi":"https://doi.org/10.1109/iscas46773.2023.10181441"},"language":"en","primary_location":{"id":"doi:10.1109/iscas46773.2023.10181441","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iscas46773.2023.10181441","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5048870090","display_name":"Runhao Li","orcid":"https://orcid.org/0000-0003-2129-9665"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Runhao Li","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Nanyang Technological University,Singapore,Singapore","School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University,Singapore,Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067922510","display_name":"Zhenyu Weng","orcid":"https://orcid.org/0000-0001-7857-8687"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Zhenyu Weng","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Nanyang Technological University,Singapore,Singapore","School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University,Singapore,Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061256037","display_name":"Huiping Zhuang","orcid":"https://orcid.org/0000-0002-4612-5445"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huiping Zhuang","raw_affiliation_strings":["Shien-Ming Wu School of Intelligent Engineering, South China University of Technology,Guangzhou,China","Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shien-Ming Wu School of Intelligent Engineering, South China University of Technology,Guangzhou,China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100428820","display_name":"Yongming Chen","orcid":"https://orcid.org/0000-0003-2843-5543"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yongming Chen","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Nanyang Technological University,Singapore,Singapore","School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University,Singapore,Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049506273","display_name":"Zhiping Lin","orcid":"https://orcid.org/0000-0002-1587-1226"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Zhiping Lin","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Nanyang Technological University,Singapore,Singapore","School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University,Singapore,Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":null,"first_page":"1","last_page":"5"},"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":0.9994999766349792,"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":0.9994999766349792,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9965999722480774,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9868999719619751,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/computer-science","display_name":"Computer science","score":0.7973083257675171},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.7006956338882446},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6883487701416016},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.6552326083183289},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6297496557235718},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6167173981666565},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4760406017303467},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.442771315574646},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40499961376190186},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3572843372821808}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7973083257675171},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.7006956338882446},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6883487701416016},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.6552326083183289},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6297496557235718},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6167173981666565},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4760406017303467},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.442771315574646},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40499961376190186},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3572843372821808},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscas46773.2023.10181441","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iscas46773.2023.10181441","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.49000000953674316}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1686810756","https://openalex.org/W1973598714","https://openalex.org/W2013535308","https://openalex.org/W2052727801","https://openalex.org/W2106277773","https://openalex.org/W2119775030","https://openalex.org/W2211092169","https://openalex.org/W2326180695","https://openalex.org/W2765440071","https://openalex.org/W2887997457","https://openalex.org/W2891461240","https://openalex.org/W2949034001","https://openalex.org/W2954672622","https://openalex.org/W2955863859","https://openalex.org/W2956018683","https://openalex.org/W2956335072","https://openalex.org/W2963514026","https://openalex.org/W2963697299","https://openalex.org/W2964155802","https://openalex.org/W2967957126","https://openalex.org/W3005680577","https://openalex.org/W3035524453","https://openalex.org/W3035546924","https://openalex.org/W3100859887","https://openalex.org/W3103717910","https://openalex.org/W3108655343","https://openalex.org/W3135179859","https://openalex.org/W3158565912","https://openalex.org/W3159476814","https://openalex.org/W3168433561","https://openalex.org/W3171635822","https://openalex.org/W3176451698","https://openalex.org/W3188030217","https://openalex.org/W4224918214","https://openalex.org/W4297808394","https://openalex.org/W4312305885","https://openalex.org/W4312382184","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6676071940","https://openalex.org/W6677994088","https://openalex.org/W6754278344","https://openalex.org/W6754596524","https://openalex.org/W6774314701","https://openalex.org/W6779145693","https://openalex.org/W6779977557","https://openalex.org/W6791471228","https://openalex.org/W6844194202"],"related_works":["https://openalex.org/W2487162673","https://openalex.org/W2793211469","https://openalex.org/W2949152769","https://openalex.org/W4372354731","https://openalex.org/W2942366970","https://openalex.org/W2807634898","https://openalex.org/W1692008701","https://openalex.org/W2597588799","https://openalex.org/W4360593462","https://openalex.org/W2562400057"],"abstract_inverted_index":{"Cross-modal":[0],"retrieval":[1,15,50],"methods":[2,16,23],"are":[3,126],"developed":[4],"to":[5,43,132],"retrieve":[6],"relevant":[7],"data":[8,37,117],"across":[9],"different":[10],"modalities.":[11],"Usually,":[12],"super-vised":[13],"cross-modal":[14,49],"can":[17,26],"achieve":[18],"higher":[19],"accuracy":[20],"than":[21],"unsupervised":[22],"because":[24],"they":[25],"utilize":[27],"the":[28,44,75,79,101,111,134],"semantic":[29],"information":[30,76],"provided":[31],"by":[32,73,118],"clean":[33],"labels.":[34],"However,":[35],"training":[36],"with":[38,88],"noisy":[39,71,104,116],"labels":[40,72,105],"will":[41],"lead":[42],"performance":[45],"degradation":[46],"of":[47,103,136],"supervised":[48],"methods.":[51],"In":[52],"this":[53],"work,":[54],"we":[55],"present":[56],"a":[57],"novel":[58],"framework":[59],"called":[60],"Neighborhood":[61,89,92],"Learning":[62],"for":[63],"Cross-Modal":[64],"Retrieval":[65],"(NLCMR)":[66],"that":[67],"is":[68],"robust":[69],"against":[70],"exploiting":[74],"contained":[77],"in":[78],"neighbor-hood.":[80],"Our":[81],"NLCMR":[82],"contains":[83],"two":[84],"main":[85],"components:":[86],"Clustering":[87],"Alignment":[90],"and":[91,106,110,121],"Contrastive":[93],"Learning.":[94],"The":[95],"first":[96],"component":[97,113],"focuses":[98],"on":[99,128],"reducing":[100],"impact":[102],"improving":[107],"clustering":[108],"robustness,":[109],"second":[112],"learns":[114],"from":[115],"exploring":[119],"pairwise":[120],"neighborhood":[122],"information.":[123],"Extensive":[124],"experiments":[125],"conducted":[127],"three":[129],"multi-modal":[130],"datasets":[131],"demonstrate":[133],"effectiveness":[135],"NLCMR.":[137]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}