{"id":"https://openalex.org/W4386495257","doi":"https://doi.org/10.1109/tpami.2023.3312749","title":"Holistically-Attracted Wireframe Parsing: From Supervised to Self-Supervised Learning","display_name":"Holistically-Attracted Wireframe Parsing: From Supervised to Self-Supervised Learning","publication_year":2023,"publication_date":"2023-09-07","ids":{"openalex":"https://openalex.org/W4386495257","doi":"https://doi.org/10.1109/tpami.2023.3312749","pmid":"https://pubmed.ncbi.nlm.nih.gov/37676811"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2023.3312749","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3312749","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/A5048981711","display_name":"Nan Xue","orcid":"https://orcid.org/0000-0002-5449-8073"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nan Xue","raw_affiliation_strings":["Ant Group, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-5449-8073","affiliations":[{"raw_affiliation_string":"Ant Group, Hangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091159460","display_name":"Tianfu Wu","orcid":"https://orcid.org/0000-0001-8911-5506"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tianfu Wu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC, USA"],"raw_orcid":"https://orcid.org/0000-0001-8911-5506","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC, USA","institution_ids":["https://openalex.org/I137902535"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101562162","display_name":"Song Bai","orcid":"https://orcid.org/0000-0002-2570-9118"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song Bai","raw_affiliation_strings":["ByteDance AI Lab, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-2570-9118","affiliations":[{"raw_affiliation_string":"ByteDance AI Lab, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011557689","display_name":"Fudong Wang","orcid":"https://orcid.org/0000-0001-6416-4707"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fu-Dong Wang","raw_affiliation_strings":["Ant Group, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-6416-4707","affiliations":[{"raw_affiliation_string":"Ant Group, Hangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073032922","display_name":"Gui-Song Xia","orcid":"https://orcid.org/0000-0001-7660-6090"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gui-Song Xia","raw_affiliation_strings":["Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-7660-6090","affiliations":[{"raw_affiliation_string":"Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100673818","display_name":"Liangpei Zhang","orcid":"https://orcid.org/0000-0001-6890-3650"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liangpei Zhang","raw_affiliation_strings":["Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-6890-3650","affiliations":[{"raw_affiliation_string":"Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042899882","display_name":"Philip H. S. Torr","orcid":null},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Philip H. S. Torr","raw_affiliation_strings":["University of Oxford, Oxford, U.K"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Oxford, Oxford, U.K","institution_ids":["https://openalex.org/I40120149"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.4911,"has_fulltext":false,"cited_by_count":40,"citation_normalized_percentile":{"value":0.96007766,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"45","issue":"12","first_page":"14727","last_page":"14744"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.9983000159263611,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9983000159263611,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9969000220298767,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9955999851226807,"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/parsing","display_name":"Parsing","score":0.7472209930419922},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7286698818206787},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.645460844039917},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.5517982840538025},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5128083825111389},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5111265778541565},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4986388683319092},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4533230662345886},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.434693306684494},{"id":"https://openalex.org/keywords/line-segment","display_name":"Line segment","score":0.41859662532806396},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.41507571935653687},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3751899003982544},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3537721633911133},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1575324833393097},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.09796112775802612}],"concepts":[{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.7472209930419922},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7286698818206787},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.645460844039917},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.5517982840538025},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5128083825111389},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5111265778541565},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4986388683319092},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4533230662345886},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.434693306684494},{"id":"https://openalex.org/C182124507","wikidata":"https://www.wikidata.org/wiki/Q166154","display_name":"Line segment","level":2,"score":0.41859662532806396},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.41507571935653687},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3751899003982544},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3537721633911133},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1575324833393097},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.09796112775802612},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2023.3312749","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3312749","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:37676811","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37676811","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":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.49000000953674316}],"awards":[{"id":"https://openalex.org/G2852671763","display_name":null,"funder_award_id":"62101390","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3965009956","display_name":null,"funder_award_id":"U22B2011","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7558576680","display_name":null,"funder_award_id":"EP/W002981/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G7875021329","display_name":null,"funder_award_id":"62325111","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"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W22745672","https://openalex.org/W639708223","https://openalex.org/W1486646730","https://openalex.org/W1498183729","https://openalex.org/W1522301498","https://openalex.org/W1944585701","https://openalex.org/W1998050452","https://openalex.org/W2079930597","https://openalex.org/W2105548357","https://openalex.org/W2108598243","https://openalex.org/W2108729336","https://openalex.org/W2110158442","https://openalex.org/W2111308925","https://openalex.org/W2124404372","https://openalex.org/W2151103935","https://openalex.org/W2160072137","https://openalex.org/W2172188317","https://openalex.org/W2307770531","https://openalex.org/W2412782625","https://openalex.org/W2476548250","https://openalex.org/W2601564443","https://openalex.org/W2604612225","https://openalex.org/W2607333215","https://openalex.org/W2798943056","https://openalex.org/W2953809838","https://openalex.org/W2955186028","https://openalex.org/W2963200201","https://openalex.org/W2963796061","https://openalex.org/W2981415272","https://openalex.org/W2989604896","https://openalex.org/W2995890703","https://openalex.org/W3035228270","https://openalex.org/W3035524453","https://openalex.org/W3043075211","https://openalex.org/W3048520814","https://openalex.org/W3096609285","https://openalex.org/W3101641457","https://openalex.org/W3104369000","https://openalex.org/W3105705379","https://openalex.org/W3106615849","https://openalex.org/W3107016113","https://openalex.org/W3155554509","https://openalex.org/W3163999715","https://openalex.org/W3167259153","https://openalex.org/W3173592916","https://openalex.org/W3185799881","https://openalex.org/W3186564193","https://openalex.org/W4214568521","https://openalex.org/W4283791382","https://openalex.org/W4289598290","https://openalex.org/W4312841185","https://openalex.org/W4313156423","https://openalex.org/W4321512640","https://openalex.org/W4385245566","https://openalex.org/W6631190155","https://openalex.org/W6651155528","https://openalex.org/W6676449312","https://openalex.org/W6697925102","https://openalex.org/W6739901393","https://openalex.org/W6760424586","https://openalex.org/W6778485988","https://openalex.org/W6785475625","https://openalex.org/W6841432534"],"related_works":["https://openalex.org/W4386442742","https://openalex.org/W2353000084","https://openalex.org/W4205730002","https://openalex.org/W2942906518","https://openalex.org/W1623138178","https://openalex.org/W4288363470","https://openalex.org/W2357946356","https://openalex.org/W180294324","https://openalex.org/W3084509788","https://openalex.org/W2353540264"],"abstract_inverted_index":{"This":[0],"article":[1],"presents":[2],"Holistically-Attracted":[3],"Wireframe":[4],"Parsing":[5],"(HAWP),":[6],"a":[7,25,37,59,94,145,151],"method":[8],"for":[9,112,154],"geometric":[10,40],"analysis":[11],"of":[12,47,62,165],"2D":[13],"images":[14,159],"containing":[15],"wireframes":[16],"formed":[17],"by":[18,52],"line":[19,34,63,77],"segments":[20,35,64,78],"and":[21,54,68,87,109,138],"junctions.":[22],"HAWP":[23,45],"utilizes":[24],"parsimonious":[26],"Holistic":[27],"Attraction":[28],"(HAT)":[29],"field":[30],"representation":[31],"that":[32,102],"encodes":[33],"using":[36],"closed-form":[38],"4D":[39],"vector":[41],"field.":[42],"The":[43],"proposed":[44],"consists":[46],"three":[48],"sequential":[49],"components":[50],"empowered":[51],"end-to-end":[53],"HAT-driven":[55],"designs:":[56],"1)":[57],"generating":[58],"dense":[60,76],"set":[61],"from":[65,71],"HAT":[66,110],"fields":[67,111],"endpoint":[69,81,107],"proposals":[70,82,92,108],"heatmaps,":[72],"2)":[73],"binding":[74],"the":[75,104],"to":[79,83,116],"sparse":[80],"produce":[84],"initial":[85],"wireframes,":[86],"3)":[88],"filtering":[89],"false":[90],"positive":[91],"through":[93],"novel":[95,118],"endpoint-decoupled":[96],"line-of-interest":[97],"aligning":[98],"(EPD":[99],"LOIAlign)":[100],"module":[101],"captures":[103],"co-occurrence":[105],"between":[106],"better":[113],"verification.":[114],"Thanks":[115],"our":[117],"designs,":[119],"HAWPv2":[120],"shows":[121],"strong":[122],"performance":[123],"in":[124,131,157],"fully":[125],"supervised":[126],"learning,":[127,133],"while":[128],"HAWPv3":[129,149],"excels":[130],"self-supervised":[132],"achieving":[134],"superior":[135],"repeatability":[136],"scores":[137],"efficient":[139],"training":[140],"(24":[141],"GPU":[142],"hours":[143],"on":[144],"single":[146],"GPU).":[147],"Furthermore,":[148],"exhibits":[150],"promising":[152],"potential":[153],"wireframe":[155],"parsing":[156],"out-of-distribution":[158],"without":[160],"providing":[161],"ground":[162],"truth":[163],"labels":[164],"wireframes.":[166]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":24},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}