{"id":"https://openalex.org/W2905904780","doi":"https://doi.org/10.1007/s41095-018-0128-6","title":"DeepPrimitive: Image decomposition by layered primitive detection","display_name":"DeepPrimitive: Image decomposition by layered primitive detection","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2905904780","doi":"https://doi.org/10.1007/s41095-018-0128-6","mag":"2905904780"},"language":"en","primary_location":{"id":"doi:10.1007/s41095-018-0128-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41095-018-0128-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41095-018-0128-6.pdf","source":{"id":"https://openalex.org/S2487656537","display_name":"Computational Visual Media","issn_l":"2096-0433","issn":["2096-0433","2096-0662"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Visual Media","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://link.springer.com/content/pdf/10.1007/s41095-018-0128-6.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070611359","display_name":"Jiahui Huang","orcid":"https://orcid.org/0000-0001-6320-2636"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiahui Huang","raw_affiliation_strings":["Tsinghua University, Beijing, 100084, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, 100084, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100776559","display_name":"Jun Gao","orcid":"https://orcid.org/0009-0005-9256-4747"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jun Gao","raw_affiliation_strings":["Computer Science Department, University of Toronto, Toronto, M5S2E4, Canada"],"affiliations":[{"raw_affiliation_string":"Computer Science Department, University of Toronto, Toronto, M5S2E4, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052129393","display_name":"Vignesh Ganapathi\u2010Subramanian","orcid":null},"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":false,"raw_author_name":"Vignesh Ganapathi-Subramanian","raw_affiliation_strings":["Stanford University, Stanford, 94305, United States","Stanford University, Stanford, 94305, USA"],"affiliations":[{"raw_affiliation_string":"Stanford University, Stanford, 94305, United States","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Stanford University, Stanford, 94305, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063492117","display_name":"Hao Su","orcid":"https://orcid.org/0000-0002-4013-7728"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hao Su","raw_affiliation_strings":["University of California San Diego, La Jolla, 92093, United States","University of California San Diego, La Jolla, 92093, USA"],"affiliations":[{"raw_affiliation_string":"University of California San Diego, La Jolla, 92093, United States","institution_ids":["https://openalex.org/I36258959"]},{"raw_affiliation_string":"University of California San Diego, La Jolla, 92093, USA","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100411682","display_name":"Yin Liu","orcid":"https://orcid.org/0009-0002-2734-6573"},"institutions":[{"id":"https://openalex.org/I4210090273","display_name":"Madison Group (United States)","ror":"https://ror.org/00aw4mh72","country_code":"US","type":"company","lineage":["https://openalex.org/I4210090273"]},{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yin Liu","raw_affiliation_strings":["University of Wisconsin-Madison, Madison, 53715, United States","University of Wisconsin-Madison, Madison, 53715, USA"],"affiliations":[{"raw_affiliation_string":"University of Wisconsin-Madison, Madison, 53715, United States","institution_ids":["https://openalex.org/I135310074","https://openalex.org/I4210090273"]},{"raw_affiliation_string":"University of Wisconsin-Madison, Madison, 53715, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082870343","display_name":"Chengcheng Tang","orcid":"https://orcid.org/0000-0002-4875-6670"},"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":false,"raw_author_name":"Chengcheng Tang","raw_affiliation_strings":["Stanford University, Stanford, 94305, United States","Stanford University, Stanford, 94305, USA"],"affiliations":[{"raw_affiliation_string":"Stanford University, Stanford, 94305, United States","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Stanford University, Stanford, 94305, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065368881","display_name":"Leonidas Guibas","orcid":"https://orcid.org/0000-0002-8315-4886"},"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":false,"raw_author_name":"Leonidas J. Guibas","raw_affiliation_strings":["Stanford University, Stanford, 94305, United States","Stanford University, Stanford, 94305, USA"],"affiliations":[{"raw_affiliation_string":"Stanford University, Stanford, 94305, United States","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Stanford University, Stanford, 94305, USA","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5070611359"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":1.0428,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.82673522,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"4","issue":"4","first_page":"385","last_page":"397"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval 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"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9976000189781189,"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/computer-science","display_name":"Computer science","score":0.7273797988891602},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.724570631980896},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6403554081916809},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6249730587005615},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5483412146568298},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.4878968894481659},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4670528173446655},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics","score":0.45856013894081116},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.41583818197250366},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3893737494945526},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3485284447669983}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7273797988891602},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.724570631980896},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6403554081916809},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6249730587005615},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5483412146568298},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.4878968894481659},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4670528173446655},{"id":"https://openalex.org/C77660652","wikidata":"https://www.wikidata.org/wiki/Q150971","display_name":"Computer graphics","level":2,"score":0.45856013894081116},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41583818197250366},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3893737494945526},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3485284447669983},{"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/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1007/s41095-018-0128-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41095-018-0128-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41095-018-0128-6.pdf","source":{"id":"https://openalex.org/S2487656537","display_name":"Computational Visual Media","issn_l":"2096-0433","issn":["2096-0433","2096-0662"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Visual Media","raw_type":"journal-article"},{"id":"pmh:oai:utoronto.scholaris.ca:1807/93541","is_oa":true,"landing_page_url":"http://hdl.handle.net/1807/93541","pdf_url":"https://utoronto.scholaris.ca/bitstreams/2b05e969-dd7d-4cea-afc7-376fe7319d42/download","source":{"id":"https://openalex.org/S7407055458","display_name":"TSpace","issn_l":null,"issn":null,"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":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"pmh:oai:doaj.org/article:712691899e18471fba421d995aa4e38c","is_oa":true,"landing_page_url":"https://doaj.org/article/712691899e18471fba421d995aa4e38c","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computational Visual Media, Vol 4, Iss 4, Pp 385-397 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s41095-018-0128-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41095-018-0128-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41095-018-0128-6.pdf","source":{"id":"https://openalex.org/S2487656537","display_name":"Computational Visual Media","issn_l":"2096-0433","issn":["2096-0433","2096-0662"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Visual Media","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7200000286102295,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G6755165505","display_name":null,"funder_award_id":"award","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6984935295","display_name":"CHS: Small: Deriving and Exploiting Shape Semantics","funder_award_id":"1528025","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8370307378","display_name":null,"funder_award_id":"IIS-1528025","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2905904780.pdf","grobid_xml":"https://content.openalex.org/works/W2905904780.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W22745672","https://openalex.org/W639708223","https://openalex.org/W648786980","https://openalex.org/W1883517952","https://openalex.org/W1976197162","https://openalex.org/W1981276685","https://openalex.org/W1992467676","https://openalex.org/W1993120651","https://openalex.org/W2049981393","https://openalex.org/W2052286413","https://openalex.org/W2071602487","https://openalex.org/W2095905764","https://openalex.org/W2108729336","https://openalex.org/W2154660120","https://openalex.org/W2156406284","https://openalex.org/W2157331557","https://openalex.org/W2170126048","https://openalex.org/W2194321275","https://openalex.org/W2526468814","https://openalex.org/W2556893918","https://openalex.org/W2559655401","https://openalex.org/W2565639579","https://openalex.org/W2570343428","https://openalex.org/W2623660146","https://openalex.org/W2736019926","https://openalex.org/W2739010165","https://openalex.org/W2949191055","https://openalex.org/W2949842255","https://openalex.org/W2951548327","https://openalex.org/W2963037989","https://openalex.org/W2964341242","https://openalex.org/W3106250896","https://openalex.org/W3150997492","https://openalex.org/W3213458668","https://openalex.org/W4234552385","https://openalex.org/W4236965008","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W3037187668","https://openalex.org/W2611989081","https://openalex.org/W4230611425","https://openalex.org/W2731899572","https://openalex.org/W2380685755","https://openalex.org/W4304166257","https://openalex.org/W3021540629","https://openalex.org/W4294635752","https://openalex.org/W2252100032"],"abstract_inverted_index":{"The":[0],"perception":[1],"of":[2,22,33,41,49,83,87,136],"the":[3,23,47,53,62,66,80,109,127],"visual":[4,24,34,42],"world":[5],"through":[6],"basic":[7],"building":[8,84],"blocks,":[9],"such":[10],"as":[11],"cubes,":[12],"spheres,":[13],"and":[14,65,144,158],"cones,":[15],"gives":[16],"human":[17],"beings":[18],"a":[19,96,104,115,133],"parsimonious":[20],"understanding":[21],"world.":[25],"Thus,":[26],"efforts":[27],"to":[28,38,46,71,98,122,129,142],"find":[29],"primitive-based":[30],"geometric":[31,85],"interpretations":[32,86],"data":[35],"date":[36],"back":[37],"1970s":[39],"studies":[40],"media.":[43],"However,":[44],"due":[45],"difficulty":[48],"primitive":[50],"fitting":[51],"in":[52,103],"pre-deep":[54],"learning":[55,92,147],"age,":[56],"this":[57,76,124],"research":[58],"approach":[59],"faded":[60],"from":[61,101],"main":[63],"stage,":[64],"vision":[67],"community":[68],"turned":[69],"primarily":[70],"semantic":[72],"image":[73],"understanding.":[74],"In":[75],"paper,":[77],"we":[78],"revisit":[79],"classical":[81],"problem":[82],"images,":[88],"using":[89],"supervised":[90],"deep":[91],"tools.":[93],"We":[94,138],"build":[95],"framework":[97],"detect":[99],"primitives":[100,131],"images":[102],"layered":[105,152],"manner":[106],"by":[107],"modifying":[108],"YOLO":[110],"network;":[111],"an":[112],"RNN":[113],"with":[114,126,132],"novel":[116],"loss":[117],"function":[118],"is":[119],"then":[120],"used":[121],"equip":[123],"network":[125],"capability":[128],"predict":[130],"variable":[134],"number":[135],"parameters.":[137],"compare":[139],"our":[140,151],"pipeline":[141],"traditional":[143],"other":[145],"baseline":[146],"methods,":[148],"demonstrating":[149],"that":[150],"detection":[153],"model":[154],"has":[155],"higher":[156],"accuracy":[157],"performs":[159],"better":[160],"reconstruction.":[161]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2020,"cited_by_count":5}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
