{"id":"https://openalex.org/W4405033747","doi":"https://doi.org/10.48550/arxiv.2412.00952","title":"ESCAPE: Equivariant Shape Completion via Anchor Point Encoding","display_name":"ESCAPE: Equivariant Shape Completion via Anchor Point Encoding","publication_year":2024,"publication_date":"2024-12-01","ids":{"openalex":"https://openalex.org/W4405033747","doi":"https://doi.org/10.48550/arxiv.2412.00952"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2412.00952","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2412.00952","pdf_url":"https://arxiv.org/pdf/2412.00952","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":null},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2412.00952","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5115003681","display_name":"Burak Bekci","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Bekci, Burak","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046896448","display_name":"Nassir Navab","orcid":"https://orcid.org/0000-0002-6032-5611"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Navab, Nassir","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041092666","display_name":"Federico Tombari","orcid":"https://orcid.org/0000-0001-5598-5212"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tombari, Federico","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5101398345","display_name":"Mahdi Saleh","orcid":"https://orcid.org/0000-0002-6690-5510"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Saleh, Mahdi","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5115003681"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9908000230789185,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9908000230789185,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9884999990463257,"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":0.9848999977111816,"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/equivariant-map","display_name":"Equivariant map","score":0.883467435836792},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.6728907227516174},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5912171602249146},{"id":"https://openalex.org/keywords/completion","display_name":"Completion (oil and gas wells)","score":0.45738309621810913},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43911775946617126},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3693828582763672},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.3456432521343231},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.2440386414527893},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.23689359426498413},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23577448725700378}],"concepts":[{"id":"https://openalex.org/C171036898","wikidata":"https://www.wikidata.org/wiki/Q256355","display_name":"Equivariant map","level":2,"score":0.883467435836792},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.6728907227516174},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5912171602249146},{"id":"https://openalex.org/C2779538338","wikidata":"https://www.wikidata.org/wiki/Q2990590","display_name":"Completion (oil and gas wells)","level":2,"score":0.45738309621810913},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43911775946617126},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3693828582763672},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.3456432521343231},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.2440386414527893},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.23689359426498413},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23577448725700378},{"id":"https://openalex.org/C46141821","wikidata":"https://www.wikidata.org/wiki/Q209402","display_name":"Nuclear magnetic resonance","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2412.00952","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2412.00952","pdf_url":"https://arxiv.org/pdf/2412.00952","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":null},{"id":"doi:10.48550/arxiv.2412.00952","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2412.00952","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:2412.00952","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2412.00952","pdf_url":"https://arxiv.org/pdf/2412.00952","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":null},"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/W2360737145","https://openalex.org/W3148895720","https://openalex.org/W2393913406","https://openalex.org/W4245777471","https://openalex.org/W4233733659","https://openalex.org/W4233380927","https://openalex.org/W2356579025","https://openalex.org/W2736697936","https://openalex.org/W3211835374","https://openalex.org/W30258475"],"abstract_inverted_index":{"Shape":[0,46],"completion,":[1],"a":[2,52,64,73,80,92,102],"crucial":[3],"task":[4],"in":[5,153],"3D":[6],"computer":[7],"vision,":[8],"involves":[9],"predicting":[10],"and":[11,30,75,107,119,148],"filling":[12],"the":[13,88,97,109,130,134],"missing":[14],"regions":[15],"of":[16,96],"scanned":[17],"or":[18,27],"partially":[19],"observed":[20],"objects.":[21],"Current":[22],"methods":[23],"expect":[24],"known":[25],"pose":[26,158],"canonical":[28],"coordinates":[29],"do":[31],"not":[32],"perform":[33,126],"well":[34],"under":[35,121],"varying":[36],"rotations,":[37],"limiting":[38],"their":[39],"real-world":[40,154],"applicability.":[41],"We":[42],"introduce":[43],"ESCAPE":[44,100,140],"(Equivariant":[45],"Completion":[47],"via":[48],"Anchor":[49],"Point":[50],"Encoding),":[51],"novel":[53],"framework":[54],"designed":[55],"to":[56,82,90,105,128],"achieve":[57],"rotation-equivariant":[58,94],"shape":[59,74,115],"completion.":[60],"Our":[61],"approach":[62],"employs":[63],"distinctive":[65],"encoding":[66],"strategy":[67],"by":[68],"selecting":[69],"anchor":[70,84],"points":[71,78],"from":[72,133],"representing":[76],"all":[77,83],"as":[79],"distance":[81,110],"points.":[85],"This":[86],"enables":[87],"model":[89],"capture":[91],"consistent,":[93],"understanding":[95],"object's":[98],"geometry.":[99],"leverages":[101],"transformer":[103],"architecture":[104],"encode":[106],"decode":[108],"transformations,":[111],"ensuring":[112],"that":[113,139],"generated":[114],"completions":[116],"remain":[117],"accurate":[118],"equivariant":[120],"rotational":[122],"transformations.":[123],"Subsequently,":[124],"we":[125],"optimization":[127],"calculate":[129],"predicted":[131],"shapes":[132],"encodings.":[135],"Experimental":[136],"evaluations":[137],"demonstrate":[138],"achieves":[141],"robust,":[142],"high-quality":[143],"reconstructions":[144],"across":[145],"arbitrary":[146],"rotations":[147],"translations,":[149],"showcasing":[150],"its":[151],"effectiveness":[152],"applications":[155],"without":[156],"additional":[157],"estimation":[159],"modules.":[160]},"counts_by_year":[],"updated_date":"2026-03-14T08:43:22.919905","created_date":"2025-10-10T00:00:00"}