{"id":"https://openalex.org/W4386075836","doi":"https://doi.org/10.1109/cvpr52729.2023.02051","title":"Self-Supervised Super-Plane for Neural 3D Reconstruction","display_name":"Self-Supervised Super-Plane for Neural 3D Reconstruction","publication_year":2023,"publication_date":"2023-06-01","ids":{"openalex":"https://openalex.org/W4386075836","doi":"https://doi.org/10.1109/cvpr52729.2023.02051"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr52729.2023.02051","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52729.2023.02051","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","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/A5024410598","display_name":"Botao Ye","orcid":"https://orcid.org/0000-0003-1676-0111"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Botao Ye","raw_affiliation_strings":["University of Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049815485","display_name":"Sifei Liu","orcid":"https://orcid.org/0000-0002-6011-3686"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sifei Liu","raw_affiliation_strings":["NVIDIA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100685997","display_name":"Xueting Li","orcid":"https://orcid.org/0000-0002-4680-6996"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xueting Li","raw_affiliation_strings":["NVIDIA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100418319","display_name":"Ming\u2013Hsuan Yang","orcid":"https://orcid.org/0000-0003-4848-2304"},"institutions":[{"id":"https://openalex.org/I156087764","display_name":"University of California, Merced","ror":"https://ror.org/00d9ah105","country_code":"US","type":"education","lineage":["https://openalex.org/I156087764"]},{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR","US"],"is_corresponding":false,"raw_author_name":"Ming-Hsuan Yang","raw_affiliation_strings":["University of California,Merced","Yonsei University","University of California, Merced"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California,Merced","institution_ids":["https://openalex.org/I156087764"]},{"raw_affiliation_string":"Yonsei University","institution_ids":["https://openalex.org/I193775966"]},{"raw_affiliation_string":"University of California, Merced","institution_ids":["https://openalex.org/I156087764"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2351,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.81861653,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"21415","last_page":"21424"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9993000030517578,"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":0.9993000030517578,"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":0.9991999864578247,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/computer-science","display_name":"Computer science","score":0.7215180993080139},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7041696310043335},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6638734936714172},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5982560515403748},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5972223281860352},{"id":"https://openalex.org/keywords/plane","display_name":"Plane (geometry)","score":0.5289608836174011},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.5168295502662659},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4996030330657959},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.49782657623291016},{"id":"https://openalex.org/keywords/surface-reconstruction","display_name":"Surface reconstruction","score":0.4551513195037842},{"id":"https://openalex.org/keywords/ground-plane","display_name":"Ground plane","score":0.4545941650867462},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.42956772446632385},{"id":"https://openalex.org/keywords/surface","display_name":"Surface (topology)","score":0.38437604904174805},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16099843382835388},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.12723731994628906}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7215180993080139},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7041696310043335},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6638734936714172},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5982560515403748},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5972223281860352},{"id":"https://openalex.org/C17825722","wikidata":"https://www.wikidata.org/wiki/Q17285","display_name":"Plane (geometry)","level":2,"score":0.5289608836174011},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.5168295502662659},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4996030330657959},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49782657623291016},{"id":"https://openalex.org/C20885615","wikidata":"https://www.wikidata.org/wiki/Q825595","display_name":"Surface reconstruction","level":3,"score":0.4551513195037842},{"id":"https://openalex.org/C88764893","wikidata":"https://www.wikidata.org/wiki/Q1547722","display_name":"Ground plane","level":3,"score":0.4545941650867462},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.42956772446632385},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.38437604904174805},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16099843382835388},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.12723731994628906},{"id":"https://openalex.org/C21822782","wikidata":"https://www.wikidata.org/wiki/Q131214","display_name":"Antenna (radio)","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr52729.2023.02051","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52729.2023.02051","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.7799999713897705,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W1482548926","https://openalex.org/W1505712405","https://openalex.org/W1522301498","https://openalex.org/W1987648924","https://openalex.org/W1989476314","https://openalex.org/W1993244675","https://openalex.org/W2008073424","https://openalex.org/W2009422376","https://openalex.org/W2074378519","https://openalex.org/W2112174119","https://openalex.org/W2116851763","https://openalex.org/W2152327564","https://openalex.org/W2171056981","https://openalex.org/W2471962767","https://openalex.org/W2519683295","https://openalex.org/W2594519801","https://openalex.org/W2895040125","https://openalex.org/W2905260191","https://openalex.org/W2917562521","https://openalex.org/W2926429807","https://openalex.org/W2962793285","https://openalex.org/W2963710007","https://openalex.org/W2964009301","https://openalex.org/W2997914516","https://openalex.org/W3012826510","https://openalex.org/W3034259269","https://openalex.org/W3034375692","https://openalex.org/W3034395814","https://openalex.org/W3034530552","https://openalex.org/W3107105757","https://openalex.org/W3154129649","https://openalex.org/W3172610252","https://openalex.org/W3202037070","https://openalex.org/W3203257492","https://openalex.org/W3203439539","https://openalex.org/W3213840695","https://openalex.org/W4200150166","https://openalex.org/W4214648559","https://openalex.org/W4233857083","https://openalex.org/W4281784082","https://openalex.org/W4287114999","https://openalex.org/W4287864845","https://openalex.org/W4297812694","https://openalex.org/W4312421564","https://openalex.org/W4312539440","https://openalex.org/W4312654682","https://openalex.org/W4312725793","https://openalex.org/W4313023430","https://openalex.org/W4313186498","https://openalex.org/W4321512716","https://openalex.org/W6629086452","https://openalex.org/W6631190155","https://openalex.org/W6647685828","https://openalex.org/W6652231383","https://openalex.org/W6669240361","https://openalex.org/W6750117916","https://openalex.org/W6772434259","https://openalex.org/W6774418182","https://openalex.org/W6774909859","https://openalex.org/W6784729325","https://openalex.org/W6785847386","https://openalex.org/W6797770180","https://openalex.org/W6798033281","https://openalex.org/W6839182500","https://openalex.org/W6839216030"],"related_works":["https://openalex.org/W4295532600","https://openalex.org/W2063823869","https://openalex.org/W2047973478","https://openalex.org/W2067569035","https://openalex.org/W2090985514","https://openalex.org/W2113666009","https://openalex.org/W2145649715","https://openalex.org/W2125566825","https://openalex.org/W3195209712","https://openalex.org/W2787993192"],"abstract_inverted_index":{"Neural":[0],"implicit":[1],"surface":[2],"representation":[3],"methods":[4],"show":[5,138],"impressive":[6],"reconstruction":[7,62,97,147,160],"results":[8,161],"but":[9],"struggle":[10],"to":[11,84,89,132],"handle":[12],"texture-less":[13],"planar":[14],"regions":[15,65],"that":[16,29,108,139],"widely":[17],"exist":[18],"in":[19],"indoor":[20],"scenes.":[21],"Existing":[22],"approaches":[23],"addressing":[24],"this":[25,39],"leverage":[26],"image":[27],"prior":[28],"requires":[30],"assistive":[31],"networks":[32],"trained":[33,111],"with":[34,112],"large-scale":[35],"annotated":[36,120],"datasets.":[37],"In":[38],"work,":[40],"we":[41,73],"introduce":[42,74],"a":[43,86,100,127],"self-supervised":[44,141],"super-plane":[45,87,101,124,142],"constraint":[46,143],"by":[47],"exploring":[48],"the":[49,54,61,95,109,116,158],"free":[50],"geometry":[51],"cues":[52],"from":[53,162],"predicted":[55],"surface,":[56],"which":[57],"can":[58,165],"further":[59],"regularize":[60],"of":[63,82,94],"plane":[64,155,159],"without":[66],"any":[67],"other":[68,171],"ground":[69,153],"truth":[70,154],"annotations.":[71],"Specifically,":[72],"an":[75],"iterative":[76],"training":[77],"scheme,":[78],"where":[79],"(i)":[80],"grouping":[81],"pixels":[83],"formulate":[85],"(analogous":[88],"super-pixels),":[90],"and":[91,130,176],"(ii)":[92],"optimizing":[93],"scene":[96],"network":[98],"via":[99],"constraint,":[102],"are":[103,178],"progressively":[104],"conducted.":[105],"We":[106],"demonstrate":[107],"model":[110,164],"superplanes":[113],"surprisingly":[114],"outperforms":[115],"one":[117],"using":[118,152],"conventional":[119],"planes,":[121],"as":[122],"individual":[123],"statistically":[125],"occupies":[126],"larger":[128],"area":[129],"leads":[131],"more":[133],"stable":[134],"training.":[135],"Extensive":[136],"experiments":[137],"our":[140,163],"significantly":[144],"improves":[145],"3D":[146],"quality":[148],"even":[149],"better":[150],"than":[151],"segmentation.":[156],"Additionally,":[157],"be":[166],"used":[167],"for":[168,170],"auto-labeling":[169],"vision":[172],"tasks.":[173],"The":[174],"code":[175],"models":[177],"available":[179],"at":[180],"https://github.com/botaoye/S3PRecon.":[181]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":6}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}