{"id":"https://openalex.org/W4283221338","doi":"https://doi.org/10.1145/3528233.3530742","title":"Unsupervised Kinematic Motion Detection for Part-segmented 3D Shape Collections","display_name":"Unsupervised Kinematic Motion Detection for Part-segmented 3D Shape Collections","publication_year":2022,"publication_date":"2022-07-20","ids":{"openalex":"https://openalex.org/W4283221338","doi":"https://doi.org/10.1145/3528233.3530742"},"language":"en","primary_location":{"id":"doi:10.1145/3528233.3530742","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3528233.3530742","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Special Interest Group on Computer Graphics and Interactive Techniques Conference Proceedings","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/A5035308844","display_name":"Xianghao Xu","orcid":"https://orcid.org/0000-0001-9822-2469"},"institutions":[{"id":"https://openalex.org/I175594653","display_name":"John Brown University","ror":"https://ror.org/02ct41q97","country_code":"US","type":"education","lineage":["https://openalex.org/I175594653"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xianghao Xu","raw_affiliation_strings":["Brown University, United States of America"],"affiliations":[{"raw_affiliation_string":"Brown University, United States of America","institution_ids":["https://openalex.org/I175594653"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037980400","display_name":"Yifan Ruan","orcid":null},"institutions":[{"id":"https://openalex.org/I175594653","display_name":"John Brown University","ror":"https://ror.org/02ct41q97","country_code":"US","type":"education","lineage":["https://openalex.org/I175594653"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yifan Ruan","raw_affiliation_strings":["Brown University, United States of America"],"affiliations":[{"raw_affiliation_string":"Brown University, United States of America","institution_ids":["https://openalex.org/I175594653"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014973945","display_name":"Srinath Sridhar","orcid":"https://orcid.org/0000-0003-4663-3324"},"institutions":[{"id":"https://openalex.org/I175594653","display_name":"John Brown University","ror":"https://ror.org/02ct41q97","country_code":"US","type":"education","lineage":["https://openalex.org/I175594653"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Srinath Sridhar","raw_affiliation_strings":["Brown University, United States of America"],"affiliations":[{"raw_affiliation_string":"Brown University, United States of America","institution_ids":["https://openalex.org/I175594653"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059267221","display_name":"Daniel Ritchie","orcid":"https://orcid.org/0000-0002-8253-0069"},"institutions":[{"id":"https://openalex.org/I175594653","display_name":"John Brown University","ror":"https://ror.org/02ct41q97","country_code":"US","type":"education","lineage":["https://openalex.org/I175594653"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel Ritchie","raw_affiliation_strings":["Brown University, United States of America"],"affiliations":[{"raw_affiliation_string":"Brown University, United States of America","institution_ids":["https://openalex.org/I175594653"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5035308844"],"corresponding_institution_ids":["https://openalex.org/I175594653"],"apc_list":null,"apc_paid":null,"fwci":1.0066,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.76514657,"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":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9997000098228455,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9997000098228455,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9994999766349792,"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/kinematics","display_name":"Kinematics","score":0.7060526609420776},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6338682770729065},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6271623373031616},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6205072999000549},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5356528162956238},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.38765162229537964},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09019938111305237}],"concepts":[{"id":"https://openalex.org/C39920418","wikidata":"https://www.wikidata.org/wiki/Q11476","display_name":"Kinematics","level":2,"score":0.7060526609420776},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6338682770729065},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6271623373031616},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6205072999000549},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5356528162956238},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.38765162229537964},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09019938111305237},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3528233.3530742","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3528233.3530742","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Special Interest Group on Computer Graphics and Interactive Techniques Conference Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.7099999785423279}],"awards":[{"id":"https://openalex.org/G642498168","display_name":null,"funder_award_id":"1941808","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1548410568","https://openalex.org/W1564897360","https://openalex.org/W1570540164","https://openalex.org/W2013666485","https://openalex.org/W2150457612","https://openalex.org/W2172156083","https://openalex.org/W2487365028","https://openalex.org/W2597507805","https://openalex.org/W2611932403","https://openalex.org/W2724314443","https://openalex.org/W2770305773","https://openalex.org/W2887358179","https://openalex.org/W2897765997","https://openalex.org/W2963515833","https://openalex.org/W2963995996","https://openalex.org/W2980109758","https://openalex.org/W3005360647","https://openalex.org/W3035131925","https://openalex.org/W3035492592","https://openalex.org/W3103783157","https://openalex.org/W3122509788","https://openalex.org/W4234552385","https://openalex.org/W4242339877","https://openalex.org/W4252024886","https://openalex.org/W4394671432","https://openalex.org/W6652416108","https://openalex.org/W6788754771","https://openalex.org/W6948176391"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398","https://openalex.org/W2775347418"],"abstract_inverted_index":{"3D":[0,75],"models":[1],"of":[2,47,92],"manufactured":[3],"objects":[4,25],"are":[5],"important":[6],"for":[7,12,16,68],"populating":[8],"virtual":[9],"worlds":[10],"and":[11,18],"synthetic":[13],"data":[14],"generation":[15],"vision":[17],"robotics.":[19],"To":[20],"be":[21,27],"most":[22],"useful,":[23],"such":[24,125],"should":[26,31,96],"articulated:":[28],"their":[29],"parts":[30,95],"move":[32],"when":[33],"interacted":[34],"with.":[35],"While":[36],"articulated":[37,70],"object":[38,99],"datasets":[39],"exist,":[40],"creating":[41],"them":[42],"is":[43,80],"labor-intensive.":[44],"Learning-based":[45],"prediction":[46,174],"part":[48,122,145],"motions":[49,71,146],"can":[50,128],"help,":[51],"but":[52],"all":[53,153],"existing":[54],"methods":[55],"require":[56],"annotated":[57],"training":[58],"data.":[59],"In":[60],"this":[61,113],"paper,":[62],"we":[63,85],"present":[64],"an":[65,93,116],"unsupervised":[66],"approach":[67,79,139],"discovering":[69],"in":[72,100,133],"a":[73,83,106,109,120],"part-segmented":[74],"shape":[76,154],"collection.":[77,135],"Our":[78],"based":[81],"on":[82],"concept":[84,114],"call":[86],"category":[87,104],"closure:":[88],"any":[89],"valid":[90],"articulation":[91],"object\u2019s":[94],"keep":[97],"the":[98,101,134,148],"same":[102],"semantic":[103],"(e.g.":[105],"chair":[107],"stays":[108],"chair).":[110],"We":[111,136],"operationalize":[112],"with":[115,164],"algorithm":[117],"that":[118,126],"optimizes":[119],"shape\u2019s":[121],"motion":[123,159,173],"parameters":[124,160],"it":[127,142],"transform":[129],"into":[130],"other":[131],"shapes":[132],"evaluate":[137],"our":[138,156],"by":[140],"using":[141],"to":[143,166],"re-discover":[144],"from":[147],"PartNet-Mobility":[149],"dataset.":[150],"For":[151],"almost":[152],"categories,":[155],"method\u2019s":[157],"predicted":[158],"have":[161],"low":[162],"error":[163],"respect":[165],"ground":[167],"truth":[168],"annotations,":[169],"outperforming":[170],"two":[171],"supervised":[172],"methods.":[175]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}