{"id":"https://openalex.org/W2045200918","doi":"https://doi.org/10.1109/wacv.2014.6836081","title":"Attribute-based vehicle recognition using viewpoint-aware multiple instance SVMs","display_name":"Attribute-based vehicle recognition using viewpoint-aware multiple instance SVMs","publication_year":2014,"publication_date":"2014-03-01","ids":{"openalex":"https://openalex.org/W2045200918","doi":"https://doi.org/10.1109/wacv.2014.6836081","mag":"2045200918"},"language":"en","primary_location":{"id":"doi:10.1109/wacv.2014.6836081","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv.2014.6836081","pdf_url":null,"source":{"id":"https://openalex.org/S4393918690","display_name":"IEEE Winter Conference on Applications of Computer Vision","issn_l":"2472-6737","issn":["2472-6737"],"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Winter Conference on Applications of Computer Vision","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/A5045314081","display_name":"Kun Duan","orcid":"https://orcid.org/0000-0003-3897-4081"},"institutions":[{"id":"https://openalex.org/I4210119109","display_name":"Indiana University Bloomington","ror":"https://ror.org/02k40bc56","country_code":"US","type":"education","lineage":["https://openalex.org/I4210119109","https://openalex.org/I592451"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kun Duan","raw_affiliation_strings":["Indiana University, Bloomington, IN, USA","Indiana University-Bloomington , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indiana University, Bloomington, IN, USA","institution_ids":["https://openalex.org/I4210119109"]},{"raw_affiliation_string":"Indiana University-Bloomington , USA","institution_ids":["https://openalex.org/I4210119109"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018191127","display_name":"Luca Marchesotti","orcid":null},"institutions":[{"id":"https://openalex.org/I33976269","display_name":"Xerox (France)","ror":"https://ror.org/033q0mv79","country_code":"FR","type":"company","lineage":["https://openalex.org/I33976269","https://openalex.org/I4210132870"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Luca Marchesotti","raw_affiliation_strings":["Xerox Research Centre Europe, Grenoble, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xerox Research Centre Europe, Grenoble, France","institution_ids":["https://openalex.org/I33976269"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003268415","display_name":"David Crandall","orcid":"https://orcid.org/0000-0002-5827-5344"},"institutions":[{"id":"https://openalex.org/I4210119109","display_name":"Indiana University Bloomington","ror":"https://ror.org/02k40bc56","country_code":"US","type":"education","lineage":["https://openalex.org/I4210119109","https://openalex.org/I592451"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David J. Crandall","raw_affiliation_strings":["Indiana University, Bloomington, IN, USA","Indiana University-Bloomington , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indiana University, Bloomington, IN, USA","institution_ids":["https://openalex.org/I4210119109"]},{"raw_affiliation_string":"Indiana University-Bloomington , USA","institution_ids":["https://openalex.org/I4210119109"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.4324,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.8799465,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"333","last_page":"338"},"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":0.9973999857902527,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9961000084877014,"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/discriminative-model","display_name":"Discriminative model","score":0.8474153876304626},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7911942005157471},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.7267681360244751},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7105517983436584},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6078264117240906},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5773199200630188},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5178297162055969},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5058104991912842},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.49276164174079895},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4112658202648163}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8474153876304626},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7911942005157471},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.7267681360244751},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7105517983436584},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6078264117240906},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5773199200630188},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5178297162055969},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5058104991912842},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.49276164174079895},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4112658202648163},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/wacv.2014.6836081","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv.2014.6836081","pdf_url":null,"source":{"id":"https://openalex.org/S4393918690","display_name":"IEEE Winter Conference on Applications of Computer Vision","issn_l":"2472-6737","issn":["2472-6737"],"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Winter Conference on Applications of Computer Vision","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.675.3830","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.675.3830","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://vision.soic.indiana.edu/papers/vehicle2014wacv.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320313934","display_name":"Institut national de recherche en informatique et en automatique (INRIA)","ror":"https://ror.org/02kvxyf05"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1528802670","https://openalex.org/W1533501036","https://openalex.org/W1969616664","https://openalex.org/W1989684337","https://openalex.org/W1994213117","https://openalex.org/W1995318441","https://openalex.org/W2045750950","https://openalex.org/W2073299621","https://openalex.org/W2076215987","https://openalex.org/W2085261163","https://openalex.org/W2103490241","https://openalex.org/W2108745803","https://openalex.org/W2117103983","https://openalex.org/W2123495974","https://openalex.org/W2128532956","https://openalex.org/W2141659202","https://openalex.org/W2147880316","https://openalex.org/W2151103935","https://openalex.org/W2151509460","https://openalex.org/W2167267877","https://openalex.org/W2168356304","https://openalex.org/W2541843346","https://openalex.org/W6631694491","https://openalex.org/W6632063742","https://openalex.org/W6649138653","https://openalex.org/W6675696936","https://openalex.org/W6676245398","https://openalex.org/W6681010617","https://openalex.org/W6682082992","https://openalex.org/W6728942955"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W3172695526","https://openalex.org/W2357114597","https://openalex.org/W2115416187","https://openalex.org/W114581555","https://openalex.org/W3098003361"],"abstract_inverted_index":{"Vehicle":[0],"recognition":[1,30],"is":[2,81],"a":[3,40],"challenging":[4],"task":[5],"with":[6,130],"many":[7],"useful":[8],"applications.":[9],"State-of-the-art":[10],"methods":[11],"usually":[12],"learn":[13],"discriminative":[14,85],"classifiers":[15],"for":[16,90],"different":[17,21],"vehicle":[18,29,91],"categories":[19],"or":[20],"viewpoint":[22,52,71,100],"angles,":[23],"but":[24],"little":[25],"work":[26],"has":[27],"explored":[28],"using":[31],"semantic":[32,87],"visual":[33],"attributes.":[34],"In":[35],"this":[36],"paper,":[37],"we":[38,97],"propose":[39],"novel":[41],"iterative":[42],"multiple":[43],"instance":[44],"learning":[45],"method":[46,80],"to":[47,65,83],"model":[48],"local":[49,88],"attributes":[50,89],"and":[51,86,124,128],"angles":[53],"together":[54],"in":[55,112],"the":[56,61,113,118,121],"same":[57],"framework.":[58],"We":[59,76,93,116],"expand":[60],"standard":[62],"MISVM":[63],"formulation":[64],"incorporate":[66],"pairwise":[67],"constraints":[68],"based":[69],"on":[70,120],"relations":[72],"within":[73],"positive":[74],"exemplars.":[75],"show":[77,95],"that":[78,96],"our":[79],"able":[82],"generate":[84],"categories.":[92],"also":[94],"can":[98],"estimate":[99],"labels":[101],"more":[102],"accurately":[103],"than":[104],"baselines":[105],"when":[106],"these":[107],"annotations":[108],"are":[109],"not":[110],"available":[111],"training":[114],"set.":[115],"test":[117],"technique":[119],"Stanford":[122],"cars":[123],"INRIA":[125],"vehicles":[126],"datasets,":[127],"compare":[129],"other":[131],"methods.":[132]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1}],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2025-10-10T00:00:00"}
