{"id":"https://openalex.org/W3093228383","doi":"https://doi.org/10.1109/icpr48806.2021.9412967","title":"Directed Variational Cross-encoder Network for Few-shot Multi-image Co-segmentation","display_name":"Directed Variational Cross-encoder Network for Few-shot Multi-image Co-segmentation","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3093228383","doi":"https://doi.org/10.1109/icpr48806.2021.9412967","mag":"3093228383"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412967","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412967","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2010.08800","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072188872","display_name":"Sayan Banerjee","orcid":"https://orcid.org/0000-0002-8586-9236"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sayan Banerjee","raw_affiliation_strings":["Indian Institute of Technology, Bombay","Indian Institute of Technology,Dept. of Electrical Engineering,Bombay"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology, Bombay","institution_ids":["https://openalex.org/I162827531"]},{"raw_affiliation_string":"Indian Institute of Technology,Dept. of Electrical Engineering,Bombay","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043941505","display_name":"S Divakar Bhat","orcid":"https://orcid.org/0000-0001-7816-7167"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"S Divakar Bhat","raw_affiliation_strings":["Indian Institute of Technology, Bombay","Indian Institute of Technology,Dept. of Electrical Engineering,Bombay"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology, Bombay","institution_ids":["https://openalex.org/I162827531"]},{"raw_affiliation_string":"Indian Institute of Technology,Dept. of Electrical Engineering,Bombay","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016405213","display_name":"Subhasis Chaudhuri","orcid":"https://orcid.org/0000-0002-1680-0016"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Subhasis Chaudhuri","raw_affiliation_strings":["Indian Institute of Technology, Bombay","Indian Institute of Technology Bombay"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology, Bombay","institution_ids":["https://openalex.org/I162827531"]},{"raw_affiliation_string":"Indian Institute of Technology Bombay","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103090020","display_name":"Rajbabu Velmurugan","orcid":"https://orcid.org/0000-0002-3511-1806"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rajbabu Velmurugan","raw_affiliation_strings":["Indian Institute of Technology, Bombay","Indian Institute of Technology Bombay"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology, Bombay","institution_ids":["https://openalex.org/I162827531"]},{"raw_affiliation_string":"Indian Institute of Technology Bombay","institution_ids":["https://openalex.org/I162827531"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I162827531"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00876307,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"8431","last_page":"8438"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9990000128746033,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9990000128746033,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9973999857902527,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9901999831199646,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.7797225713729858},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7749984264373779},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.7471886873245239},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6702019572257996},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6550953388214111},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6167306900024414},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5974879264831543},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.521395742893219},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4653269648551941},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42279762029647827}],"concepts":[{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7797225713729858},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7749984264373779},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.7471886873245239},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6702019572257996},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6550953388214111},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6167306900024414},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5974879264831543},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.521395742893219},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4653269648551941},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42279762029647827},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412967","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412967","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2010.08800","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2010.08800","pdf_url":"https://arxiv.org/pdf/2010.08800","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":"mag:3093228383","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2010.08800","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2010.08800","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2010.08800","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":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2010.08800","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2010.08800","pdf_url":"https://arxiv.org/pdf/2010.08800","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":[{"id":"https://metadata.un.org/sdg/4","score":0.41999998688697815,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3093228383.pdf","grobid_xml":"https://content.openalex.org/works/W3093228383.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W1533861849","https://openalex.org/W1964884769","https://openalex.org/W1984034752","https://openalex.org/W1996140089","https://openalex.org/W2225156818","https://openalex.org/W2295160225","https://openalex.org/W2601450892","https://openalex.org/W2740660291","https://openalex.org/W2752782242","https://openalex.org/W2754560798","https://openalex.org/W2773771410","https://openalex.org/W2797333655","https://openalex.org/W2806918713","https://openalex.org/W2807912089","https://openalex.org/W2884585870","https://openalex.org/W2891177538","https://openalex.org/W2893918048","https://openalex.org/W2896011443","https://openalex.org/W2963420686","https://openalex.org/W2963495494","https://openalex.org/W2963599420","https://openalex.org/W2965004577","https://openalex.org/W2965555521","https://openalex.org/W2981787211","https://openalex.org/W2983850069","https://openalex.org/W2990230185","https://openalex.org/W2990844506","https://openalex.org/W2994528761","https://openalex.org/W3101380508","https://openalex.org/W6631943919","https://openalex.org/W6735236233","https://openalex.org/W6753412334","https://openalex.org/W6754568377"],"related_works":["https://openalex.org/W3163760587","https://openalex.org/W3191820386","https://openalex.org/W3165845133","https://openalex.org/W2291422229","https://openalex.org/W3035680157","https://openalex.org/W3180833442","https://openalex.org/W3000358855","https://openalex.org/W3176239531","https://openalex.org/W3167453437","https://openalex.org/W2105893331","https://openalex.org/W3130064502","https://openalex.org/W2769439543","https://openalex.org/W2803489489","https://openalex.org/W2408429073","https://openalex.org/W2888340395","https://openalex.org/W3085685449","https://openalex.org/W3212561242","https://openalex.org/W3145474143","https://openalex.org/W2960677377","https://openalex.org/W2981537222"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,121],"propose":[4],"a":[5,23,36,50,61,69,115],"novel":[6,37,70],"framework":[7,94],"for":[8,29],"multi-image":[9],"co-segmentation":[10,83],"using":[11,113],"class":[12,100,105],"agnostic":[13],"meta-learning":[14],"strategy":[15],"by":[16],"generalizing":[17],"to":[18,54,74],"new":[19,31],"classes":[20],"given":[21],"only":[22,114],"small":[24,77,85,116],"number":[25],"of":[26,63,118],"training":[27,119],"samples":[28],"each":[30],"class.":[32],"We":[33,59],"have":[34,122],"developed":[35],"encoder-decoder":[38],"network":[39,67],"termed":[40],"as":[41],"DVICE":[42,66],"(Directed":[43],"Variational":[44],"Inference":[45],"Cross":[46],"Encoder),":[47],"which":[48],"learns":[49],"continuous":[51],"embedding":[52],"space":[53],"ensure":[55],"better":[56],"similarity":[57],"learning.":[58],"employ":[60],"combination":[62],"the":[64,76,92],"proposed":[65,93],"and":[68,89,102],"few-shot":[71],"learning":[72],"approach":[73,126],"tackle":[75],"sample":[78],"size":[79],"problem":[80],"encountered":[81],"in":[82],"with":[84],"datasets":[86,112],"like":[87],"iCoseg":[88],"MSRC.":[90],"Furthermore,":[91],"does":[95],"not":[96],"use":[97],"any":[98],"semantic":[99],"labels":[101],"is":[103],"entirely":[104],"agnostic.":[106],"Through":[107],"exhaustive":[108],"experimentation":[109],"over":[110],"multiple":[111],"volume":[117],"data,":[120],"demonstrated":[123],"that":[124],"our":[125],"outperforms":[127],"all":[128],"existing":[129],"state-of-the-art":[130],"techniques.":[131]},"counts_by_year":[],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2025-10-10T00:00:00"}
