{"id":"https://openalex.org/W2143729633","doi":"https://doi.org/10.1109/iccv.2011.6126282","title":"Extracting adaptive contextual cues from unlabeled regions","display_name":"Extracting adaptive contextual cues from unlabeled regions","publication_year":2011,"publication_date":"2011-11-01","ids":{"openalex":"https://openalex.org/W2143729633","doi":"https://doi.org/10.1109/iccv.2011.6126282","mag":"2143729633"},"language":"en","primary_location":{"id":"doi:10.1109/iccv.2011.6126282","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2011.6126282","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 International Conference on Computer Vision","raw_type":"proceedings-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/A5100332234","display_name":"Congcong Li","orcid":"https://orcid.org/0000-0001-8126-6211"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Congcong Li","raw_affiliation_strings":["Cornell University, USA","Cornell University,USA"],"affiliations":[{"raw_affiliation_string":"Cornell University, USA","institution_ids":["https://openalex.org/I205783295"]},{"raw_affiliation_string":"Cornell University,USA","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050342343","display_name":"Devi Parikh","orcid":null},"institutions":[{"id":"https://openalex.org/I160992636","display_name":"Toyota Technological Institute at Chicago","ror":"https://ror.org/02sn5gb64","country_code":"US","type":"education","lineage":["https://openalex.org/I160992636"]},{"id":"https://openalex.org/I4840577","display_name":"Toyota Technological Institute","ror":"https://ror.org/001hv0k59","country_code":"JP","type":"education","lineage":["https://openalex.org/I4840577"]}],"countries":["JP","US"],"is_corresponding":false,"raw_author_name":"Devi Parikh","raw_affiliation_strings":["Toyota Technological Institute Chicago","[Toyota Technological Institute, Chicago, USA]"],"affiliations":[{"raw_affiliation_string":"Toyota Technological Institute Chicago","institution_ids":["https://openalex.org/I160992636"]},{"raw_affiliation_string":"[Toyota Technological Institute, Chicago, USA]","institution_ids":["https://openalex.org/I4840577"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000454484","display_name":"Tsuhan Chen","orcid":"https://orcid.org/0000-0003-3951-7931"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tsuhan Chen","raw_affiliation_strings":["Cornell University, USA","Cornell University,USA"],"affiliations":[{"raw_affiliation_string":"Cornell University, USA","institution_ids":["https://openalex.org/I205783295"]},{"raw_affiliation_string":"Cornell University,USA","institution_ids":["https://openalex.org/I205783295"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100332234"],"corresponding_institution_ids":["https://openalex.org/I205783295"],"apc_list":null,"apc_paid":null,"fwci":7.8943,"has_fulltext":false,"cited_by_count":38,"citation_normalized_percentile":{"value":0.97333733,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"511","last_page":"518"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.991100013256073,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.991100013256073,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9854000210762024,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9531999826431274,"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/computer-science","display_name":"Computer science","score":0.6841158866882324},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5506948828697205},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40393465757369995},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3233262896537781}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6841158866882324},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5506948828697205},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40393465757369995},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3233262896537781}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/iccv.2011.6126282","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2011.6126282","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 International Conference on Computer Vision","raw_type":"proceedings-article"},{"id":"pmh:oai:scholarbank.nus.edu.sg:10635/146147","is_oa":false,"landing_page_url":"http://scholarbank.nus.edu.sg/handle/10635/146147","pdf_url":null,"source":{"id":"https://openalex.org/S7407052290","display_name":"National University of Singapore","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Scopus","raw_type":"Conference Paper"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.371.1242","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.371.1242","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://chenlab.ece.cornell.edu/people/congcong/publications/ICCV2011_AdaptiveContext.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.372.794","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.372.794","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://filebox.ece.vt.edu/~parikh/Publications/LiParikhChen_ICCV2011_unlabeled.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.5,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1516887802","https://openalex.org/W1560380655","https://openalex.org/W1982522767","https://openalex.org/W1995444699","https://openalex.org/W2031489346","https://openalex.org/W2046589395","https://openalex.org/W2048088055","https://openalex.org/W2049705550","https://openalex.org/W2077493928","https://openalex.org/W2081293863","https://openalex.org/W2098355199","https://openalex.org/W2102905523","https://openalex.org/W2106848651","https://openalex.org/W2106962004","https://openalex.org/W2110306668","https://openalex.org/W2120419212","https://openalex.org/W2121043743","https://openalex.org/W2128962821","https://openalex.org/W2130942329","https://openalex.org/W2137971795","https://openalex.org/W2141364309","https://openalex.org/W2142037471","https://openalex.org/W2146352414","https://openalex.org/W2160254296","https://openalex.org/W2161969291","https://openalex.org/W2162820221","https://openalex.org/W2166761907","https://openalex.org/W2167090521","https://openalex.org/W2168356304","https://openalex.org/W2538008885","https://openalex.org/W4241222664","https://openalex.org/W6630825005","https://openalex.org/W6633519119","https://openalex.org/W6674646328","https://openalex.org/W6681508479"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2772917594","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398","https://openalex.org/W2775347418"],"abstract_inverted_index":{"Existing":[0],"approaches":[1],"to":[2,17,27,45,95,105,142],"contextual":[3,19,69,89,99],"reasoning":[4],"for":[5],"enhanced":[6],"object":[7,117,133,162],"detection":[8],"typically":[9,56],"utilize":[10],"other":[11],"labeled":[12],"categories":[13],"in":[14,33,75],"the":[15,28,34,40,48,81,97,143,165],"images":[16,41],"provide":[18],"information.":[20],"As":[21],"a":[22,68,103,107,119,154,160],"consequence,":[23],"they":[24],"inadvertently":[25],"commit":[26],"granularity":[29,82],"of":[30,39,47,110,121,157],"information":[31,90],"implicit":[32],"labels.":[35],"Moreover,":[36],"large":[37],"portions":[38],"may":[42],"not":[43],"belong":[44],"any":[46,131],"manually-chosen":[49],"categories,":[50],"and":[51,66,112],"these":[52,64],"unlabeled":[53,73],"regions":[54,74],"are":[55],"neglected.":[57],"In":[58,93],"this":[59],"paper,":[60],"we":[61,101],"overcome":[62],"both":[63],"drawbacks":[65],"propose":[67],"cue":[70,139,152],"that":[71,148],"exploits":[72],"images.":[76],"Our":[77,145],"approach":[78],"adaptively":[79],"determines":[80],"(scene,":[83],"inter-object,":[84],"intra-object,":[85],"etc.)":[86],"at":[87],"which":[88,135],"is":[91,118],"captured.":[92],"order":[94],"extract":[96],"proposed":[98,127,138,151],"cue,":[100],"consider":[102],"scene":[104],"be":[106],"structured":[108],"configuration":[109],"objects":[111],"regions;":[113],"just":[114],"as":[115],"an":[116],"composition":[120],"parts.":[122],"We":[123],"thus":[124],"learn":[125],"our":[126,137,150],"\u201ccontextual":[128],"meta-objects\u201d":[129],"using":[130],"off-the-shelf":[132],"detector,":[134],"makes":[136],"widely":[140],"accessible":[141],"community.":[144],"results":[146],"show":[147],"incorporating":[149],"provides":[153],"relative":[155],"improvement":[156],"12%":[158],"over":[159],"state-of-the-art":[161],"detector":[163],"on":[164],"challenging":[166],"PASCAL":[167],"dataset.":[168]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":7},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":7},{"year":2012,"cited_by_count":4}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
