{"id":"https://openalex.org/W1976323859","doi":"https://doi.org/10.1109/cvpr.2011.5995571","title":"A hierarchical conditional random field model for labeling and segmenting images of street scenes","display_name":"A hierarchical conditional random field model for labeling and segmenting images of street scenes","publication_year":2011,"publication_date":"2011-06-01","ids":{"openalex":"https://openalex.org/W1976323859","doi":"https://doi.org/10.1109/cvpr.2011.5995571","mag":"1976323859"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2011.5995571","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2011.5995571","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"CVPR 2011","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/A5056540212","display_name":"Qixing Huang","orcid":"https://orcid.org/0000-0001-6365-8051"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Qixing Huang","raw_affiliation_strings":["University of Stanford, USA","Stanford University"],"affiliations":[{"raw_affiliation_string":"University of Stanford, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Stanford University","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100774500","display_name":"Mei Han","orcid":"https://orcid.org/0000-0002-3123-2205"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mei Han","raw_affiliation_strings":["Google, Inc., USA","GOOGLE INC "],"affiliations":[{"raw_affiliation_string":"Google, Inc., USA","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"GOOGLE INC ","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059368105","display_name":"Bo Wu","orcid":"https://orcid.org/0000-0001-6658-6452"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bo Wu","raw_affiliation_strings":["Google, Inc., USA","GOOGLE INC "],"affiliations":[{"raw_affiliation_string":"Google, Inc., USA","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"GOOGLE INC ","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032800189","display_name":"Sergey Ioffe","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sergey Ioffe","raw_affiliation_strings":["Google, Inc., USA","GOOGLE INC "],"affiliations":[{"raw_affiliation_string":"Google, Inc., USA","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"GOOGLE INC ","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5056540212"],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":6.2781,"has_fulltext":false,"cited_by_count":56,"citation_normalized_percentile":{"value":0.97134139,"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":"1953","last_page":"1960"},"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":0.9998999834060669,"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":0.9998999834060669,"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":0.9998000264167786,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9988999962806702,"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/conditional-random-field","display_name":"Conditional random field","score":0.881502628326416},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7876523733139038},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6785916090011597},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6524285078048706},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6091631650924683},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.606848418712616},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5842676758766174},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.580577552318573},{"id":"https://openalex.org/keywords/market-segmentation","display_name":"Market segmentation","score":0.5653852224349976},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5240378975868225},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5163437128067017},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.46207383275032043},{"id":"https://openalex.org/keywords/hierarchical-database-model","display_name":"Hierarchical database model","score":0.41667240858078003},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19975918531417847},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.13617396354675293},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.13218116760253906},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.08490115404129028}],"concepts":[{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.881502628326416},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7876523733139038},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6785916090011597},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6524285078048706},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6091631650924683},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.606848418712616},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5842676758766174},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.580577552318573},{"id":"https://openalex.org/C125308379","wikidata":"https://www.wikidata.org/wiki/Q363057","display_name":"Market segmentation","level":2,"score":0.5653852224349976},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5240378975868225},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5163437128067017},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.46207383275032043},{"id":"https://openalex.org/C144986985","wikidata":"https://www.wikidata.org/wiki/Q871236","display_name":"Hierarchical database model","level":2,"score":0.41667240858078003},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19975918531417847},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.13617396354675293},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.13218116760253906},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.08490115404129028},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/cvpr.2011.5995571","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2011.5995571","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"CVPR 2011","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.294.6544","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.294.6544","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://static.googleusercontent.com/external_content/untrusted_dlcp/research.google.com/en/us/pubs/archive/37125.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.687.320","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.687.320","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://graphics.stanford.edu/%7Ehuangqx/cvpr11.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.6499999761581421,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1528789833","https://openalex.org/W1532257412","https://openalex.org/W1542723449","https://openalex.org/W1548953334","https://openalex.org/W1748750709","https://openalex.org/W2067191022","https://openalex.org/W2081293863","https://openalex.org/W2095844239","https://openalex.org/W2110764733","https://openalex.org/W2114915823","https://openalex.org/W2116877738","https://openalex.org/W2125849446","https://openalex.org/W2128554449","https://openalex.org/W2141739106","https://openalex.org/W2155871590","https://openalex.org/W2160254296","https://openalex.org/W2162915993","https://openalex.org/W2171011251","https://openalex.org/W2171188998","https://openalex.org/W4240726888","https://openalex.org/W6631412525","https://openalex.org/W6632547051","https://openalex.org/W6632792525","https://openalex.org/W6637730771","https://openalex.org/W6674793120","https://openalex.org/W6678684981"],"related_works":["https://openalex.org/W2356597680","https://openalex.org/W2093471820","https://openalex.org/W50079190","https://openalex.org/W2114846443","https://openalex.org/W3102147106","https://openalex.org/W2378211422","https://openalex.org/W2347460059","https://openalex.org/W2111726165","https://openalex.org/W4321353415","https://openalex.org/W2745001401"],"abstract_inverted_index":{"Simultaneously":[0],"segmenting":[1],"and":[2,57,76,98,114],"labeling":[3,27,67,93,115,125],"images":[4,28,51,56],"is":[5,95],"a":[6,17,41,59,68],"fundamental":[7],"problem":[8,25],"in":[9,99],"Computer":[10],"Vision.":[11],"In":[12,37,110],"this":[13,84,90],"paper,":[14],"we":[15,49,71,117],"introduce":[16],"hierarchical":[18,91],"CRF":[19,42,60,80],"model":[20,43,61,81],"to":[21,39,82,112,121,127],"deal":[22],"with":[23],"the":[24,46,73,78,123],"of":[26,29,54],"street":[30],"scenes":[31],"by":[32],"several":[33],"distinctive":[34],"object":[35],"classes.":[36],"addition":[38,111],"learning":[40],"from":[44,62],"all":[45],"labeled":[47],"images,":[48],"group":[50],"into":[52],"clusters":[53],"similar":[55,130],"learn":[58],"each":[63],"cluster":[64,75],"separately.":[65],"When":[66],"new":[69],"image,":[70],"pick":[72],"closest":[74],"use":[77],"associated":[79],"label":[83],"image.":[85],"Experimental":[86],"results":[87],"show":[88],"that":[89],"image":[92,124],"method":[94],"comparable":[96],"to,":[97,103],"many":[100],"cases":[101],"superior":[102],"previous":[104],"methods":[105],"on":[106],"benchmark":[107],"data":[108],"sets.":[109],"segmentation":[113],"results,":[116],"also":[118],"showed":[119],"how":[120],"apply":[122],"result":[126],"rerank":[128],"Google":[129],"images.":[131]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":7},{"year":2016,"cited_by_count":10},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":12},{"year":2013,"cited_by_count":7},{"year":2012,"cited_by_count":4}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}