{"id":"https://openalex.org/W4403750109","doi":"https://doi.org/10.48550/arxiv.2407.12479","title":"SENC: Handling Self-collision in Neural Cloth Simulation","display_name":"SENC: Handling Self-collision in Neural Cloth Simulation","publication_year":2024,"publication_date":"2024-07-17","ids":{"openalex":"https://openalex.org/W4403750109","doi":"https://doi.org/10.48550/arxiv.2407.12479"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2407.12479","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2407.12479","pdf_url":"https://arxiv.org/pdf/2407.12479","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2407.12479","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062569341","display_name":"Zhouyingcheng Liao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liao, Zhouyingcheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002674785","display_name":"Sinan Wang","orcid":"https://orcid.org/0009-0005-9322-2351"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Sinan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5014324841","display_name":"Taku Komura","orcid":"https://orcid.org/0000-0002-2729-5860"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Komura, Taku","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.864300012588501,"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"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.864300012588501,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/collision","display_name":"Collision","score":0.7999461889266968},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.48095956444740295},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.12622347474098206}],"concepts":[{"id":"https://openalex.org/C121704057","wikidata":"https://www.wikidata.org/wiki/Q352070","display_name":"Collision","level":2,"score":0.7999461889266968},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48095956444740295},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.12622347474098206}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2407.12479","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2407.12479","pdf_url":"https://arxiv.org/pdf/2407.12479","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2407.12479","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2407.12479","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2407.12479","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2407.12479","pdf_url":"https://arxiv.org/pdf/2407.12479","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W3113932901","https://openalex.org/W4396701345","https://openalex.org/W650625605","https://openalex.org/W2376932109"],"abstract_inverted_index":{"We":[0,147],"present":[1],"SENC,":[2],"a":[3,60,103],"novel":[4,61],"self-supervised":[5,36,92],"neural":[6,37,93,106],"cloth":[7,14,50,77,98,164],"simulator":[8,94],"that":[9,79,117,132,160],"addresses":[10],"the":[11,23,46,72,76,81,134,138,149],"challenge":[12],"of":[13,109,151],"self-collision.":[15],"This":[16,69],"problem":[17],"has":[18],"remained":[19],"unresolved":[20],"due":[21],"to":[22,111,136,143],"gap":[24],"in":[25,141],"simulation":[26,135],"setup":[27],"between":[28],"recent":[29],"collision":[30],"detection":[31],"and":[32,35,156],"response":[33,142],"approaches":[34],"simulators.":[38],"The":[39],"former":[40],"requires":[41],"collision-free":[42],"initial":[43],"setups,":[44],"while":[45,166],"latter":[47],"necessitates":[48],"random":[49,144],"instantiation":[51],"during":[52],"training.":[53],"To":[54],"tackle":[55],"this":[56,89],"issue,":[57],"we":[58,101,125],"propose":[59],"loss":[62,70],"based":[63,87],"on":[64,88],"Global":[65],"Intersection":[66],"Analysis":[67],"(GIA).":[68],"extracts":[71],"volume":[73],"surrounded":[74],"by":[75],"region":[78],"forms":[80],"penetration.":[82],"By":[83],"constructing":[84],"an":[85,127],"energy":[86],"volume,":[90],"our":[91],"can":[95],"effectively":[96,162],"address":[97],"self-collisions.":[99],"Moreover,":[100],"develop":[102],"self-collision-aware":[104],"graph":[105],"network":[107],"capable":[108],"learning":[110],"handle":[112],"self-collisions,":[113],"even":[114],"for":[115],"parts":[116],"are":[118],"topologically":[119],"distant":[120],"from":[121],"one":[122],"another.":[123],"Additionally,":[124],"introduce":[126],"effective":[128],"external":[129,145],"force":[130],"scheme":[131],"enables":[133],"learn":[137],"cloth's":[139],"behavior":[140],"forces.":[146],"validate":[148],"efficacy":[150],"SENC":[152],"through":[153],"extensive":[154],"quantitative":[155],"qualitative":[157],"experiments,":[158],"demonstrating":[159],"it":[161],"reduces":[163],"self-collision":[165],"maintaining":[167],"high-quality":[168],"animation":[169],"results.":[170]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-10-10T00:00:00"}
