{"id":"https://openalex.org/W4362500631","doi":"https://doi.org/10.1109/tpami.2023.3263867","title":"Learning by Restoring Broken 3D Geometry","display_name":"Learning by Restoring Broken 3D Geometry","publication_year":2023,"publication_date":"2023-04-03","ids":{"openalex":"https://openalex.org/W4362500631","doi":"https://doi.org/10.1109/tpami.2023.3263867","pmid":"https://pubmed.ncbi.nlm.nih.gov/37030814"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2023.3263867","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3263867","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5101470754","display_name":"Jinxian Liu","orcid":"https://orcid.org/0000-0002-4162-4528"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jinxian Liu","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014362734","display_name":"Bingbing Ni","orcid":"https://orcid.org/0000-0001-7339-028X"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bingbing Ni","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100359144","display_name":"Ye Chen","orcid":"https://orcid.org/0009-0002-4011-593X"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ye Chen","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061038696","display_name":"Zhenbo Yu","orcid":"https://orcid.org/0000-0003-1310-5728"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenbo Yu","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100459515","display_name":"Hang Wang","orcid":"https://orcid.org/0000-0003-0417-9258"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hang Wang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101470754"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.6365,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.60281425,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"45","issue":"9","first_page":"11024","last_page":"11039"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9998999834060669,"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":0.9998999834060669,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9980999827384949,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.781617283821106},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7766197919845581},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.73835688829422},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7167782783508301},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6883445978164673},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6170852184295654},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5446223616600037},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5249590873718262},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.46811383962631226},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.46564042568206787},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4372240900993347},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.41782698035240173},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.4104987382888794},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3590337932109833},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.19951385259628296},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15460503101348877}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.781617283821106},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7766197919845581},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.73835688829422},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7167782783508301},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6883445978164673},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6170852184295654},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5446223616600037},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5249590873718262},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.46811383962631226},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.46564042568206787},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4372240900993347},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.41782698035240173},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.4104987382888794},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3590337932109833},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.19951385259628296},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15460503101348877},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2023.3263867","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3263867","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:37030814","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37030814","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7599999904632568,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1576204990","display_name":null,"funder_award_id":"61976137","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G805875641","display_name":null,"funder_award_id":"U20B2072","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":97,"referenced_works":["https://openalex.org/W219040644","https://openalex.org/W343636949","https://openalex.org/W1923184257","https://openalex.org/W2145038566","https://openalex.org/W2229637417","https://openalex.org/W2321533354","https://openalex.org/W2326925005","https://openalex.org/W2460657278","https://openalex.org/W2487442924","https://openalex.org/W2546066744","https://openalex.org/W2550462002","https://openalex.org/W2553307952","https://openalex.org/W2558661413","https://openalex.org/W2560609797","https://openalex.org/W2594519801","https://openalex.org/W2769312834","https://openalex.org/W2785325870","https://openalex.org/W2788158258","https://openalex.org/W2795374598","https://openalex.org/W2796426482","https://openalex.org/W2797997528","https://openalex.org/W2798270772","https://openalex.org/W2798297823","https://openalex.org/W2806332096","https://openalex.org/W2888754481","https://openalex.org/W2889300857","https://openalex.org/W2895472109","https://openalex.org/W2904332125","https://openalex.org/W2910792243","https://openalex.org/W2949671016","https://openalex.org/W2954258401","https://openalex.org/W2961368225","https://openalex.org/W2962728572","https://openalex.org/W2963035165","https://openalex.org/W2963053547","https://openalex.org/W2963121255","https://openalex.org/W2963125977","https://openalex.org/W2963158438","https://openalex.org/W2963182550","https://openalex.org/W2963226018","https://openalex.org/W2963231572","https://openalex.org/W2963312728","https://openalex.org/W2963333168","https://openalex.org/W2963420272","https://openalex.org/W2963509914","https://openalex.org/W2963517242","https://openalex.org/W2963719584","https://openalex.org/W2963830382","https://openalex.org/W2964228567","https://openalex.org/W2979750740","https://openalex.org/W2981983525","https://openalex.org/W2983098675","https://openalex.org/W2985088149","https://openalex.org/W2988715931","https://openalex.org/W2990613095","https://openalex.org/W2991485494","https://openalex.org/W3005680577","https://openalex.org/W3009750677","https://openalex.org/W3010623357","https://openalex.org/W3034459762","https://openalex.org/W3035060554","https://openalex.org/W3035524453","https://openalex.org/W3035625567","https://openalex.org/W3108655343","https://openalex.org/W3109154950","https://openalex.org/W3109636218","https://openalex.org/W3110047846","https://openalex.org/W3116155584","https://openalex.org/W3116959466","https://openalex.org/W3118644257","https://openalex.org/W3119708198","https://openalex.org/W3122633743","https://openalex.org/W3128750067","https://openalex.org/W3166573884","https://openalex.org/W3173636389","https://openalex.org/W3185933454","https://openalex.org/W3206429150","https://openalex.org/W3207145355","https://openalex.org/W3214794298","https://openalex.org/W3217122878","https://openalex.org/W4200412188","https://openalex.org/W4288623616","https://openalex.org/W4394671432","https://openalex.org/W6687484953","https://openalex.org/W6729001083","https://openalex.org/W6739778489","https://openalex.org/W6747899497","https://openalex.org/W6748208425","https://openalex.org/W6754849088","https://openalex.org/W6755466756","https://openalex.org/W6758371058","https://openalex.org/W6763103765","https://openalex.org/W6763422710","https://openalex.org/W6765299845","https://openalex.org/W6774314701","https://openalex.org/W6779326418","https://openalex.org/W6781976409"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W2110523656","https://openalex.org/W1482209366","https://openalex.org/W4387272257"],"abstract_inverted_index":{"The":[0,153],"key":[1],"point":[2,105],"for":[3],"an":[4,90],"experienced":[5],"craftsman":[6],"to":[7,42,84,108,114,119,126,141,163],"repair":[8],"broken":[9,67],"objects":[10],"effectively":[11],"is":[12,40,139],"that":[13,23,117,185,198],"he":[14],"must":[15],"know":[16],"about":[17],"them":[18,125],"deeply.":[19],"Similarly,":[20],"we":[21,55,81],"believe":[22],"a":[24,32,57,76,104],"model":[25,138],"can":[26],"capture":[27,142],"rich":[28,148],"geometry":[29],"information":[30],"from":[31,79],"shape/scene":[33],"and":[34,48,96,122,150,166,173,181],"generate":[35],"discriminative":[36],"representations":[37,155],"if":[38],"it":[39],"able":[41],"find":[43],"distorted":[44,120],"parts":[45,88,121],"of":[46,89,207],"shapes/scenes":[47,68],"restore":[49],"them.":[50],"Inspired":[51],"by":[52,65,157],"this":[53,158],"observation,":[54],"propose":[56],"novel":[58],"self-supervised":[59,159],"3D":[60,71],"learning":[61,64],"paradigm":[62,160],"named":[63],"restoring":[66],"(collectively":[69],"called":[70],"geometry).":[72],"We":[73,194],"first":[74],"develop":[75],"destroy-method":[77],"cluster,":[78],"which":[80,111],"sample":[82],"methods":[83],"break":[85],"some":[86],"local":[87],"object.":[91],"Then":[92],"the":[93,97,137,205],"destroyed":[94],"object":[95,99,144,154],"normal":[98],"are":[100,112],"both":[101],"sent":[102],"into":[103],"cloud":[106],"network":[107],"get":[109],"representations,":[110],"employed":[113],"segment":[115],"points":[116],"belong":[118],"further":[123],"reconstruct/restore":[124],"normal.":[127],"To":[128],"perform":[129,167],"better":[130],"in":[131],"these":[132],"two":[133],"associated":[134],"pretext":[135],"tasks,":[136],"constrained":[140],"useful":[143],"features,":[145],"such":[146],"as":[147],"geometric":[149],"contextual":[151],"information.":[152],"learned":[156],"transfer":[161],"well":[162,168],"different":[164],"datasets":[165,180,183],"on":[169,178],"downstream":[170],"classification,":[171],"segmentation":[172],"detection":[174],"tasks.":[175],"Experimental":[176],"results":[177],"shape":[179],"scene":[182],"demonstrate":[184],"our":[186,201],"method":[187],"achieves":[188],"state-of-the-art":[189],"performance":[190,206],"among":[191],"unsupervised":[192],"methods.":[193],"also":[195],"show":[196],"experimentally":[197],"pre-training":[199],"with":[200],"framework":[202],"significantly":[203],"boosts":[204],"supervised":[208],"models.":[209]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
