{"id":"https://openalex.org/W1968485689","doi":"https://doi.org/10.1109/cvpr.2012.6247945","title":"Learning 3D object templates by hierarchical quantization of geometry and appearance spaces","display_name":"Learning 3D object templates by hierarchical quantization of geometry and appearance spaces","publication_year":2012,"publication_date":"2012-06-01","ids":{"openalex":"https://openalex.org/W1968485689","doi":"https://doi.org/10.1109/cvpr.2012.6247945","mag":"1968485689"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2012.6247945","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2012.6247945","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Conference on Computer Vision and Pattern Recognition","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/A5101505071","display_name":"Wenze Hu","orcid":"https://orcid.org/0000-0001-5516-7092"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Wenze Hu","raw_affiliation_strings":["Department of Statistics, UCLA, USA","Department of Statistics, UCLA"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, UCLA, USA","institution_ids":[]},{"raw_affiliation_string":"Department of Statistics, UCLA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101505071"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.2216,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.88738354,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2336","last_page":"2343"},"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":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval 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/T10036","display_name":"Advanced Neural Network Applications","score":0.9987999796867371,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/template","display_name":"Template","score":0.9174712896347046},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6631194949150085},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6551104187965393},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5733942985534668},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.47245386242866516},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4288516044616699},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.4220007061958313},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.28365853428840637}],"concepts":[{"id":"https://openalex.org/C82714645","wikidata":"https://www.wikidata.org/wiki/Q438331","display_name":"Template","level":2,"score":0.9174712896347046},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6631194949150085},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6551104187965393},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5733942985534668},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.47245386242866516},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4288516044616699},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.4220007061958313},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28365853428840637},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cvpr.2012.6247945","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2012.6247945","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.741.4337","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.741.4337","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.stat.ucla.edu/%7Esczhu/papers/Conf_2012/Car_3D_modeling_CVPR2012.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.49000000953674316}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1646038686","https://openalex.org/W1977045647","https://openalex.org/W2000433020","https://openalex.org/W2061488089","https://openalex.org/W2079930597","https://openalex.org/W2099972257","https://openalex.org/W2111187045","https://openalex.org/W2112074816","https://openalex.org/W2123456673","https://openalex.org/W2124386111","https://openalex.org/W2125799637","https://openalex.org/W2131225894","https://openalex.org/W2144657325","https://openalex.org/W2145757385","https://openalex.org/W2147629985","https://openalex.org/W2148999380","https://openalex.org/W2155217696","https://openalex.org/W2156406284","https://openalex.org/W2319958627","https://openalex.org/W2535401692","https://openalex.org/W2546526894","https://openalex.org/W4205969993","https://openalex.org/W4210469146","https://openalex.org/W4234899042","https://openalex.org/W4285719527","https://openalex.org/W6665803544","https://openalex.org/W6681433155","https://openalex.org/W6729258895"],"related_works":["https://openalex.org/W2121300814","https://openalex.org/W4234406076","https://openalex.org/W1886613375","https://openalex.org/W4236081792","https://openalex.org/W4250583430","https://openalex.org/W2010731026","https://openalex.org/W2360893094","https://openalex.org/W4236036386","https://openalex.org/W3091442679","https://openalex.org/W4234773973"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,21,82,90,113,144],"method":[4,124],"for":[5],"learning":[6,77],"3D":[7,16,36,94,128],"object":[8,13],"templates":[9,32],"from":[10],"view":[11,136],"labeled":[12],"images.":[14],"The":[15],"template":[17,44,95],"is":[18,45],"defined":[19],"in":[20],"joint":[22],"appearance":[23,71],"and":[24,38,57,70,107,131,135],"geometry":[25,69],"space":[26],"composed":[27],"of":[28,41,72],"deformable":[29],"planar":[30],"part":[31,43,73],"placed":[33],"at":[34],"different":[35],"positions":[37],"orientations.":[39],"Appearance":[40],"each":[42],"represented":[46],"by":[47],"Gabor":[48],"filters,":[49],"which":[50,148],"are":[51,62,140],"hierarchically":[52],"grouped":[53],"into":[54],"line":[55],"segments":[56],"geometric":[58],"shapes.":[59],"AND-OR":[60,101],"trees":[61,102],"further":[63],"used":[64],"to":[65],"quantize":[66],"the":[67,92,100,122],"possible":[68],"templates,":[74,130],"so":[75],"that":[76,121],"can":[78,96,125],"be":[79,97],"done":[80],"on":[81,112,143],"subsampled":[83],"discrete":[84],"space.":[85],"Using":[86],"information":[87],"gain":[88],"as":[89],"criterion,":[91],"best":[93],"searched":[98],"through":[99],"using":[103],"one":[104,108],"bottom-up":[105],"pass":[106],"top-down":[109],"pass.":[110],"Experiments":[111,139],"new":[114],"car":[115,129,146],"dataset":[116],"with":[117,152],"diverse":[118],"views":[119],"show":[120,149],"proposed":[123],"learn":[126],"meaningful":[127],"give":[132],"satisfactory":[133],"detection":[134],"estimation":[137],"performance.":[138],"also":[141],"performed":[142],"public":[145],"dataset,":[147],"comparable":[150],"performance":[151],"recent":[153],"methods.":[154]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":5}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
