{"id":"https://openalex.org/W1955371424","doi":"https://doi.org/10.1109/cvpr.2015.7298985","title":"Image parsing with a wide range of classes and scene-level context","display_name":"Image parsing with a wide range of classes and scene-level context","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W1955371424","doi":"https://doi.org/10.1109/cvpr.2015.7298985","mag":"1955371424"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2015.7298985","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2015.7298985","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1510.07136","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057117277","display_name":"Marian George","orcid":null},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":true,"raw_author_name":"Marian George","raw_affiliation_strings":["Department of Computer Science, ETH Zurich, Switzerland","Department of Computer Science ETH Zurich, Switzerland"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, ETH Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]},{"raw_affiliation_string":"Department of Computer Science ETH Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5057117277"],"corresponding_institution_ids":["https://openalex.org/I35440088"],"apc_list":null,"apc_paid":null,"fwci":4.4923,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.96402712,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"16","issue":null,"first_page":"3622","last_page":"3630"},"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":0.9997000098228455,"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":0.9997000098228455,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9987000226974487,"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":0.9973000288009644,"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/parsing","display_name":"Parsing","score":0.8085436224937439},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8084242939949036},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7016222476959229},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6121464371681213},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6031641960144043},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.574681282043457},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5200493335723877},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4952775537967682},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4494296908378601},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4256623685359955},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4115905165672302},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34729474782943726}],"concepts":[{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.8085436224937439},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8084242939949036},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7016222476959229},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6121464371681213},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6031641960144043},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.574681282043457},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5200493335723877},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4952775537967682},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4494296908378601},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4256623685359955},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4115905165672302},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34729474782943726},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/cvpr.2015.7298985","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2015.7298985","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1510.07136","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1510.07136","pdf_url":"https://arxiv.org/pdf/1510.07136","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":"pmh:oai:CiteSeerX.psu:10.1.1.698.2901","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.698.2901","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.vs.inf.ethz.ch/publ/papers/mageorge_parsing_cvpr2015.pdf","raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1510.07136","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1510.07136","pdf_url":"https://arxiv.org/pdf/1510.07136","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":[{"display_name":"Affordable and clean energy","score":0.6299999952316284,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1516887802","https://openalex.org/W1528789833","https://openalex.org/W1546961578","https://openalex.org/W1581592866","https://openalex.org/W1590510366","https://openalex.org/W1913356549","https://openalex.org/W1971410590","https://openalex.org/W1981283549","https://openalex.org/W1982872386","https://openalex.org/W1999478155","https://openalex.org/W2019778169","https://openalex.org/W2030346542","https://openalex.org/W2051179318","https://openalex.org/W2051458493","https://openalex.org/W2054103873","https://openalex.org/W2066941820","https://openalex.org/W2071027807","https://openalex.org/W2081293863","https://openalex.org/W2083597815","https://openalex.org/W2101309634","https://openalex.org/W2102734279","https://openalex.org/W2103956678","https://openalex.org/W2113137767","https://openalex.org/W2116445618","https://openalex.org/W2137881638","https://openalex.org/W2143516773","https://openalex.org/W2143884379","https://openalex.org/W2147609308","https://openalex.org/W2153423793","https://openalex.org/W2154083146","https://openalex.org/W2154644822","https://openalex.org/W2158275940","https://openalex.org/W2158305599","https://openalex.org/W2169177311","https://openalex.org/W2535516436","https://openalex.org/W2951702175","https://openalex.org/W3097096317","https://openalex.org/W3184458996","https://openalex.org/W4244914727","https://openalex.org/W6630825005","https://openalex.org/W6631412525","https://openalex.org/W6635091746","https://openalex.org/W6635258101","https://openalex.org/W6639824712","https://openalex.org/W6663568183","https://openalex.org/W6675876930","https://openalex.org/W6680357304","https://openalex.org/W6681469950","https://openalex.org/W6682521699","https://openalex.org/W6997266731"],"related_works":["https://openalex.org/W579810227","https://openalex.org/W2952780262","https://openalex.org/W2979495269","https://openalex.org/W2392917763","https://openalex.org/W2083429127","https://openalex.org/W2358855848","https://openalex.org/W2142145894","https://openalex.org/W2033808215","https://openalex.org/W2494523064","https://openalex.org/W4307623130"],"abstract_inverted_index":{"This":[0,41],"paper":[1],"presents":[2],"a":[3,81],"nonparametric":[4],"scene":[5,22],"parsing":[6,63],"approach":[7],"that":[8],"improves":[9],"the":[10,16,27,43,48,62,92,112],"overall":[11,93],"accuracy,":[12],"as":[13,15],"well":[14],"coverage":[17],"of":[18,50,57],"foreground":[19],"classes":[20],"in":[21,61],"images.":[23],"We":[24,96,107],"first":[25],"improve":[26],"label":[28,67],"likelihood":[29,35,83],"estimates":[30],"at":[31],"superpixels":[32],"by":[33],"merging":[34],"scores":[36],"from":[37],"different":[38],"probabilistic":[39],"classifiers.":[40],"boosts":[42],"classification":[44],"performance":[45,110],"and":[46,105,115],"enriches":[47],"representation":[49],"less-represented":[51],"classes.":[52],"Our":[53,69],"second":[54],"contribution":[55],"consists":[56],"incorporating":[58],"semantic":[59],"context":[60],"process":[64],"through":[65],"global":[66,82],"costs.":[68],"method":[70],"does":[71],"not":[72],"rely":[73],"on":[74,100,111,118],"image":[75],"retrieval":[76],"sets":[77],"but":[78],"rather":[79],"assigns":[80],"estimate":[84],"to":[85],"each":[86],"label,":[87],"which":[88],"is":[89],"plugged":[90],"into":[91],"energy":[94],"function.":[95],"evaluate":[97],"our":[98],"system":[99],"two":[101],"large-scale":[102],"datasets,":[103],"SIFTflow":[104,113],"LMSun.":[106,119],"achieve":[108],"state-of-the-art":[109],"dataset":[114],"near-record":[116],"results":[117]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":9},{"year":2016,"cited_by_count":8},{"year":2015,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
