{"id":"https://openalex.org/W2963369474","doi":"https://doi.org/10.1109/iccv.2017.103","title":"3D-PRNN: Generating Shape Primitives with Recurrent Neural Networks","display_name":"3D-PRNN: Generating Shape Primitives with Recurrent Neural Networks","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2963369474","doi":"https://doi.org/10.1109/iccv.2017.103","mag":"2963369474"},"language":"en","primary_location":{"id":"doi:10.1109/iccv.2017.103","doi":"https://doi.org/10.1109/iccv.2017.103","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2017.103","pdf_url":null,"source":{"id":"https://openalex.org/S4363607764","display_name":"IEEE/CVF International Conference on Computer Vision (ICCV)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"2017 IEEE International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1708.01648","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038747486","display_name":"Chuhang Zou","orcid":"https://orcid.org/0000-0003-2537-284X","observed_orcids":["https://orcid.org/0000-0003-2537-284X"]},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chuhang Zou","raw_affiliation_strings":["University of Illinois, Urbana-Champaign"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois, Urbana-Champaign","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028817790","display_name":"Ersin Yumer","orcid":"https://orcid.org/0000-0002-3245-5515","observed_orcids":["https://orcid.org/0000-0002-3245-5515"]},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ersin Yumer","raw_affiliation_strings":["Adobe Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Adobe Research","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jimei Yang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jimei Yang","raw_affiliation_strings":["Adobe Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Adobe Research","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068985412","display_name":"Duygu Ceylan","orcid":"https://orcid.org/0000-0002-2307-9052","observed_orcids":["https://orcid.org/0000-0002-2307-9052","https://orcid.org/0000-0001-6530-4556"]},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Duygu Ceylan","raw_affiliation_strings":["Adobe Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Adobe Research","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009682734","display_name":"Derek Hoiem","orcid":"https://orcid.org/0000-0001-6260-5708","observed_orcids":["https://orcid.org/0000-0001-6260-5708"]},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Derek Hoiem","raw_affiliation_strings":["University of Illinois, Urbana-Champaign"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois, Urbana-Champaign","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":12.0294,"has_fulltext":true,"cited_by_count":202,"citation_normalized_percentile":{"value":0.98752728,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"900","last_page":"909"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.0003000000142492354,"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":0.0003000000142492354,"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/shape-synthesis","display_name":"shape synthesis","score":0.47999998927116394},{"id":"https://openalex.org/keywords/recurrent-neural-networks","display_name":"recurrent neural networks","score":0.8349999785423279},{"id":"https://openalex.org/keywords/generative-models","display_name":"generative models","score":0.7120000123977661},{"id":"https://openalex.org/keywords/depth-maps","display_name":"depth images","score":0.8270000219345093},{"id":"https://openalex.org/keywords/symmetry","display_name":"symmetry","score":0.46299999952316284},{"id":"https://openalex.org/keywords/gaussian-random-fields","display_name":"Gaussian random fields","score":0.6800000071525574},{"id":"https://openalex.org/keywords/shape-retrieval","display_name":"shape retrieval","score":0.7609999775886536},{"id":"https://openalex.org/keywords/3d-shape-generation","display_name":"3D shape generation","score":0.42899999022483826}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7389627695083618},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6841391324996948},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6616246700286865},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.55440354347229},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5008747577667236},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4998612403869629},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.47799697518348694},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4747258424758911},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4689454734325409},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4664302170276642},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4662171006202698},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.44134989380836487},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.43447232246398926},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.42193931341171265},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4142412841320038},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15999028086662292},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"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/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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iccv.2017.103","doi":"https://doi.org/10.1109/iccv.2017.103","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2017.103","pdf_url":null,"source":{"id":"https://openalex.org/S4363607764","display_name":"IEEE/CVF International Conference on Computer Vision (ICCV)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"2017 IEEE International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1708.01648","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1708.01648","pdf_url":"https://arxiv.org/pdf/1708.01648","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"doi:10.48550/arxiv.1708.01648","doi":"https://doi.org/10.48550/arxiv.1708.01648","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1708.01648","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1708.01648","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1708.01648","pdf_url":"https://arxiv.org/pdf/1708.01648","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G331763074","display_name":"RI: Small: Recovering Object 3D Shape and Material from Isolated Images","funder_award_id":"1421521","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4211722790","display_name":null,"funder_award_id":"N00014-16-1-2007","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G574697057","display_name":null,"funder_award_id":"N00014-16-1-2007","funder_id":"https://openalex.org/F4320333591","funder_display_name":"Multidisciplinary University Research Initiative"},{"id":"https://openalex.org/G8876996369","display_name":null,"funder_award_id":"N00014","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320333591","display_name":"Multidisciplinary University Research Initiative","ror":null},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2963369474.pdf","grobid_xml":"https://content.openalex.org/works/W2963369474.grobid-xml"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W125693051","https://openalex.org/W1026270304","https://openalex.org/W1522301498","https://openalex.org/W1579853615","https://openalex.org/W1810943226","https://openalex.org/W1815076433","https://openalex.org/W1850742715","https://openalex.org/W1920022804","https://openalex.org/W1927784829","https://openalex.org/W1978235861","https://openalex.org/W1987648924","https://openalex.org/W2005126631","https://openalex.org/W2005175937","https://openalex.org/W2010625607","https://openalex.org/W2023657303","https://openalex.org/W2026687385","https://openalex.org/W2030682703","https://openalex.org/W2031760064","https://openalex.org/W2049981393","https://openalex.org/W2052976238","https://openalex.org/W2057316718","https://openalex.org/W2071634722","https://openalex.org/W2072752234","https://openalex.org/W2075922179","https://openalex.org/W2091297047","https://openalex.org/W2121975222","https://openalex.org/W2138643214","https://openalex.org/W2146727960","https://openalex.org/W2148953571","https://openalex.org/W2156406284","https://openalex.org/W2157953764","https://openalex.org/W2194775991","https://openalex.org/W2267126114","https://openalex.org/W2327562811","https://openalex.org/W2335364074","https://openalex.org/W2342277278","https://openalex.org/W2345308174","https://openalex.org/W2401306363","https://openalex.org/W2444097022","https://openalex.org/W2469266052","https://openalex.org/W2551540143","https://openalex.org/W2557269700","https://openalex.org/W2949896890","https://openalex.org/W2962741254","https://openalex.org/W2963730200","https://openalex.org/W2963951231","https://openalex.org/W2964121744","https://openalex.org/W4237306303","https://openalex.org/W4252405433","https://openalex.org/W4252410105","https://openalex.org/W4256269467","https://openalex.org/W4385483256","https://openalex.org/W6729687604","https://openalex.org/W6855100223"],"related_works":["https://openalex.org/W2948437166","https://openalex.org/W3193727918","https://openalex.org/W4412590219","https://openalex.org/W3138005505","https://openalex.org/W7167687300","https://openalex.org/W6981271062","https://openalex.org/W3093041308","https://openalex.org/W2738835886","https://openalex.org/W2604493845","https://openalex.org/W3125893632"],"abstract_inverted_index":{"The":[0],"success":[1],"of":[2,18,30,33,39,57,74,77,85,96,118,134],"various":[3],"applications":[4],"including":[5],"robotics,":[6],"digital":[7],"content":[8],"creation,":[9],"and":[10,15,93,136,146],"visualization":[11],"demand":[12],"a":[13,37,53,63,75,100,106,114,131,155],"structured":[14],"abstract":[16,46],"representation":[17,48],"the":[19,28],"3D":[20,34],"world":[21],"from":[22],"limited":[23],"sensor":[24],"data.":[25],"Inspired":[26],"by":[27],"nature":[29],"human":[31],"perception":[32],"shapes":[35,72],"as":[36],"collection":[38],"simple":[40],"parts,":[41],"we":[42,60],"explore":[43],"such":[44],"an":[45,58],"shape":[47,120,143],"based":[49,108,142],"on":[50,109,130],"primitives.":[51,78],"Given":[52],"single":[54],"depth":[55],"image":[56],"object,":[59],"present":[61],"3DPRNN,":[62],"generative":[64,80,151],"recurrent":[65],"neural":[66],"network":[67],"that":[68,138],"synthesizes":[69],"multiple":[70],"plausible":[71],"composed":[73],"set":[76],"Our":[79],"model":[81],"encodes":[82],"symmetry":[83],"characteristics":[84],"common":[86],"man-made":[87],"objects,":[88],"preserves":[89],"long-range":[90],"structural":[91],"coherence,":[92],"describes":[94],"objects":[95],"varying":[97],"complexity":[98],"with":[99,149],"compact":[101],"representation.":[102],"We":[103,126],"also":[104],"propose":[105],"method":[107],"Gaussian":[110],"Fields":[111],"to":[112,122],"generate":[113],"large":[115],"scale":[116],"dataset":[117],"primitive-based":[119],"representations":[121],"train":[123],"our":[124,128],"network.":[125],"evaluate":[127],"approach":[129],"wide":[132],"range":[133],"examples":[135],"show":[137],"it":[139],"outperforms":[140],"nearest-neighbor":[141],"retrieval":[144],"methods":[145],"is":[147],"on-par":[148],"voxelbased":[150],"models":[152],"while":[153],"using":[154],"significantly":[156],"reduced":[157],"parameter":[158],"space.":[159]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":20},{"year":2023,"cited_by_count":25},{"year":2022,"cited_by_count":24},{"year":2021,"cited_by_count":38},{"year":2020,"cited_by_count":32},{"year":2019,"cited_by_count":32},{"year":2018,"cited_by_count":11}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2019-07-30T00:00:00"}