{"id":"https://openalex.org/W4399251886","doi":"https://doi.org/10.1109/3dv69130.2026.00146","title":"Improved Convex Decomposition with Ensembling and Negative Primitives","display_name":"Improved Convex Decomposition with Ensembling and Negative Primitives","publication_year":2026,"publication_date":"2026-03-20","ids":{"openalex":"https://openalex.org/W4399251886","doi":"https://doi.org/10.1109/3dv69130.2026.00146"},"language":"en","primary_location":{"id":"doi:10.1109/3dv69130.2026.00146","is_oa":false,"landing_page_url":"https://doi.org/10.1109/3dv69130.2026.00146","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on 3D Vision (3DV)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2405.19569","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032247327","display_name":"Vaibhav Vavilala","orcid":null},"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":"Vaibhav Vavilala","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/A5035308938","display_name":"Florian Kluger","orcid":"https://orcid.org/0000-0002-8557-5238"},"institutions":[{"id":"https://openalex.org/I114112103","display_name":"Leibniz University Hannover","ror":"https://ror.org/0304hq317","country_code":"DE","type":"education","lineage":["https://openalex.org/I114112103"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Florian Kluger","raw_affiliation_strings":["Leibniz Universit&#x00E4;t Hannover"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Leibniz Universit&#x00E4;t Hannover","institution_ids":["https://openalex.org/I114112103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036391027","display_name":"Seemandhar Jain","orcid":"https://orcid.org/0000-0002-4176-3595"},"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":"Seemandhar Jain","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/A5040412734","display_name":"Bodo Rosenhahn","orcid":"https://orcid.org/0000-0003-3861-1424"},"institutions":[{"id":"https://openalex.org/I114112103","display_name":"Leibniz University Hannover","ror":"https://ror.org/0304hq317","country_code":"DE","type":"education","lineage":["https://openalex.org/I114112103"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bodo Rosenhahn","raw_affiliation_strings":["Leibniz Universit&#x00E4;t Hannover"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Leibniz Universit&#x00E4;t Hannover","institution_ids":["https://openalex.org/I114112103"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Anand Bhattad","orcid":null},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anand Bhattad","raw_affiliation_strings":["Johns Hopkins University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Johns Hopkins University","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"last","author":{"id":null,"display_name":"David Forsyth","orcid":null},"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":"David Forsyth","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":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00058981,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1534","last_page":"1544"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11797","display_name":"graph theory and CDMA systems","score":0.978600025177002,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T11797","display_name":"graph theory and CDMA systems","score":0.978600025177002,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T10963","display_name":"Advanced Optimization Algorithms Research","score":0.9760000109672546,"subfield":{"id":"https://openalex.org/subfields/2612","display_name":"Numerical Analysis"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12923","display_name":"Digital Image Processing Techniques","score":0.9498999714851379,"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/decomposition","display_name":"Decomposition","score":0.7853174209594727},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.6851614713668823},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.532950758934021},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.39127781987190247},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.37623587250709534},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.09243640303611755}],"concepts":[{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.7853174209594727},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.6851614713668823},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.532950758934021},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.39127781987190247},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37623587250709534},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.09243640303611755},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/3dv69130.2026.00146","is_oa":false,"landing_page_url":"https://doi.org/10.1109/3dv69130.2026.00146","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on 3D Vision (3DV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2405.19569","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2405.19569","pdf_url":"https://arxiv.org/pdf/2405.19569","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2405.19569","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2405.19569","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2405.19569","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2405.19569","pdf_url":"https://arxiv.org/pdf/2405.19569","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G539587745","display_name":null,"funder_award_id":"2106825","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"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4399251886.pdf","grobid_xml":"https://content.openalex.org/works/W4399251886.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W4391375266","https://openalex.org/W1979597421","https://openalex.org/W2007980826","https://openalex.org/W2061531152","https://openalex.org/W3002753104","https://openalex.org/W2077600819","https://openalex.org/W2142036596","https://openalex.org/W2072657027","https://openalex.org/W2600246793"],"abstract_inverted_index":{"Describing":[0],"a":[1,13,61,67,72,79,99,132,192],"scene":[2],"in":[3,167,170,191],"terms":[4],"of":[5,18,33,56,71,75,147],"primitives":[6,37,140,151,180],"-":[7,20],"geometrically":[8],"simple":[9],"shapes":[10],"that":[11,119,134,162],"offer":[12],"parsimonious":[14],"but":[15],"accurate":[16],"abstraction":[17],"structure":[19],"is":[21,186],"an":[22],"established":[23],"and":[24,35,49,86,141,149,173,177],"difficult":[25],"fitting":[26,127,182],"problem.":[27,128],"Different":[28],"scenes":[29],"require":[30],"different":[31],"numbers":[32],"primitives,":[34,76,106],"these":[36,138],"interact":[38],"strongly.":[39],"Existing":[40],"methods":[41],"are":[42,95,108],"evaluated":[43],"by":[44,78,98,152],"comparing":[45],"predicted":[46],"depth,":[47],"normals,":[48],"segmentation":[50,174],"against":[51],"ground":[52],"truth.":[53],"The":[54],"state":[55],"the":[57,84,111,117,120,126,144,157],"art":[58],"method":[59,81,133,185],"involves":[60],"learned":[62],"regression":[63],"procedure":[64],"to":[65,82],"predict":[66],"start":[68],"point":[69],"consisting":[70],"fixed":[73],"number":[74,146],"followed":[77],"descent":[80],"refine":[83],"geometry":[85,118],"remove":[87],"redundant":[88],"primitives.":[89,113],"CSG":[90],"(Constructive":[91],"Solid":[92],"Geometry)":[93],"representations":[94],"significantly":[96],"enhanced":[97],"set-differencing":[100],"operation.":[101],"Our":[102,184],"representation":[103,172],"incorporates":[104],"negative":[105,139,150,179],"which":[107],"differenced":[109],"from":[110],"positive":[112,148],"These":[114],"notably":[115],"enrich":[116],"model":[121],"can":[122,135],"encode,":[123],"while":[124],"complicating":[125],"This":[129],"paper":[130],"presents":[131],"(a)":[136,163],"incorporate":[137],"(b)":[142,178],"choose":[143],"overall":[145],"ensembling.":[153],"Extensive":[154],"experiments":[155],"on":[156],"standard":[158],"NYUv2":[159],"dataset":[160],"confirm":[161],"this":[164],"approach":[165],"results":[166],"substantial":[168],"improvements":[169],"depth":[171],"over":[175],"SOTA":[176],"improve":[181],"accuracy.":[183],"robustly":[187],"applicable":[188],"across":[189],"datasets:":[190],"first,":[193],"we":[194],"evaluate":[195],"primitive":[196],"prediction":[197],"for":[198],"LAION":[199],"images.":[200]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
