{"id":"https://openalex.org/W4385327947","doi":"https://doi.org/10.1145/3581783.3612136","title":"PNT-Edge: Towards Robust Edge Detection with Noisy Labels by Learning Pixel-level Noise Transitions","display_name":"PNT-Edge: Towards Robust Edge Detection with Noisy Labels by Learning Pixel-level Noise Transitions","publication_year":2023,"publication_date":"2023-10-26","ids":{"openalex":"https://openalex.org/W4385327947","doi":"https://doi.org/10.1145/3581783.3612136"},"language":"en","primary_location":{"id":"doi:10.1145/3581783.3612136","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3612136","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2307.14070","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103145956","display_name":"Wenjie Xuan","orcid":"https://orcid.org/0000-0003-1579-2218"},"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":"Wenjie Xuan","raw_affiliation_strings":["Wuhan University, Wuhan, Hubei, China"],"raw_orcid":"https://orcid.org/0000-0003-1579-2218","affiliations":[{"raw_affiliation_string":"Wuhan University, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101873694","display_name":"Shanshan Zhao","orcid":"https://orcid.org/0000-0003-0682-8645"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shanshan Zhao","raw_affiliation_strings":["JD Explore Academy, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0682-8645","affiliations":[{"raw_affiliation_string":"JD Explore Academy, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101885414","display_name":"Yu Yao","orcid":"https://orcid.org/0000-0001-9797-364X"},"institutions":[{"id":"https://openalex.org/I4210113480","display_name":"Mohamed bin Zayed University of Artificial Intelligence","ror":"https://ror.org/0258gkt32","country_code":"AE","type":"education","lineage":["https://openalex.org/I4210113480"]},{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["AE","US"],"is_corresponding":false,"raw_author_name":"Yu Yao","raw_affiliation_strings":["Mohamed bin Zayed University of Artificial Intelligence &amp; Carnegie Mellon University, Abu Dhabi, UAE"],"raw_orcid":"https://orcid.org/0000-0001-9797-364X","affiliations":[{"raw_affiliation_string":"Mohamed bin Zayed University of Artificial Intelligence &amp; Carnegie Mellon University, Abu Dhabi, UAE","institution_ids":["https://openalex.org/I4210113480","https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026501335","display_name":"Juhua Liu","orcid":"https://orcid.org/0000-0002-3907-8820"},"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":"Juhua Liu","raw_affiliation_strings":["Wuhan University, Wuhan, Hubei, China"],"raw_orcid":"https://orcid.org/0000-0002-3907-8820","affiliations":[{"raw_affiliation_string":"Wuhan University, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065250332","display_name":"Tongliang Liu","orcid":"https://orcid.org/0000-0002-9640-6472"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Tongliang Liu","raw_affiliation_strings":["The University of Sydney, Sydney, NSW, Australia"],"raw_orcid":"https://orcid.org/0000-0002-9640-6472","affiliations":[{"raw_affiliation_string":"The University of Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100393445","display_name":"Yixin Chen","orcid":"https://orcid.org/0000-0002-3704-4432"},"institutions":[{"id":"https://openalex.org/I204465549","display_name":"Washington University in St. Louis","ror":"https://ror.org/01yc7t268","country_code":"US","type":"education","lineage":["https://openalex.org/I204465549"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yixin Chen","raw_affiliation_strings":["Washington University in St. Louis, St. Louis, MO, USA"],"raw_orcid":"https://orcid.org/0000-0002-3704-4432","affiliations":[{"raw_affiliation_string":"Washington University in St. Louis, St. Louis, MO, USA","institution_ids":["https://openalex.org/I204465549"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060042752","display_name":"Bo Du","orcid":"https://orcid.org/0000-0002-0059-8458"},"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":"Bo Du","raw_affiliation_strings":["Wuhan University, Wuhan, Hubei, China"],"raw_orcid":"https://orcid.org/0000-0002-0059-8458","affiliations":[{"raw_affiliation_string":"Wuhan University, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074103823","display_name":"Dacheng Tao","orcid":"https://orcid.org/0000-0001-7225-5449"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Dacheng Tao","raw_affiliation_strings":["The University of Sydney, Sydney, NSW, Australia"],"raw_orcid":"https://orcid.org/0000-0001-7225-5449","affiliations":[{"raw_affiliation_string":"The University of Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I129604602"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1924","last_page":"1932"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.988099992275238,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9769999980926514,"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/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.7180100679397583},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6820674538612366},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6465602517127991},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.6374710202217102},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6170840859413147},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5777450203895569},{"id":"https://openalex.org/keywords/canny-edge-detector","display_name":"Canny edge detector","score":0.45733338594436646},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.45582258701324463},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4357357323169708},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.19568023085594177},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.16811823844909668}],"concepts":[{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.7180100679397583},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6820674538612366},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6465602517127991},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.6374710202217102},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6170840859413147},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5777450203895569},{"id":"https://openalex.org/C14705441","wikidata":"https://www.wikidata.org/wiki/Q597183","display_name":"Canny edge detector","level":5,"score":0.45733338594436646},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45582258701324463},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4357357323169708},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.19568023085594177},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.16811823844909668}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3581783.3612136","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3612136","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2307.14070","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2307.14070","pdf_url":"https://arxiv.org/pdf/2307.14070","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":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2307.14070","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2307.14070","pdf_url":"https://arxiv.org/pdf/2307.14070","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":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.8299999833106995}],"awards":[{"id":"https://openalex.org/G1836220556","display_name":null,"funder_award_id":"62225113","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8527334069","display_name":null,"funder_award_id":"62076186","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/F4320324116","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385327947.pdf","grobid_xml":"https://content.openalex.org/works/W4385327947.grobid-xml"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W603908379","https://openalex.org/W1514928307","https://openalex.org/W1579634341","https://openalex.org/W2110158442","https://openalex.org/W2129587342","https://openalex.org/W2144794286","https://openalex.org/W2145023731","https://openalex.org/W2300687442","https://openalex.org/W2340897893","https://openalex.org/W2474152637","https://openalex.org/W2612690371","https://openalex.org/W2622100130","https://openalex.org/W2885139206","https://openalex.org/W2885593519","https://openalex.org/W2904856451","https://openalex.org/W2952793010","https://openalex.org/W2963096987","https://openalex.org/W2963307106","https://openalex.org/W2963342403","https://openalex.org/W2964292098","https://openalex.org/W2965289249","https://openalex.org/W2966401131","https://openalex.org/W2967052791","https://openalex.org/W2980061058","https://openalex.org/W2982631194","https://openalex.org/W2990886896","https://openalex.org/W3033272814","https://openalex.org/W3035433720","https://openalex.org/W3103846556","https://openalex.org/W3106651317","https://openalex.org/W3142871063","https://openalex.org/W3196904728","https://openalex.org/W3208526321","https://openalex.org/W3216325077","https://openalex.org/W4226513344","https://openalex.org/W4241071816","https://openalex.org/W4250533120","https://openalex.org/W4286908677","https://openalex.org/W4287757781","https://openalex.org/W4312440249","https://openalex.org/W4312616451","https://openalex.org/W4312710812","https://openalex.org/W4313036592"],"related_works":["https://openalex.org/W3169126738","https://openalex.org/W2558559991","https://openalex.org/W1994279415","https://openalex.org/W1986338341","https://openalex.org/W2545065926","https://openalex.org/W2980082320","https://openalex.org/W2036421992","https://openalex.org/W3093839383","https://openalex.org/W2128085731","https://openalex.org/W4293054829"],"abstract_inverted_index":{"Relying":[0],"on":[1,150],"large-scale":[2],"training":[3],"data":[4],"with":[5,145],"pixel-level":[6],"labels,":[7],"previous":[8],"edge":[9,51,59,121],"detection":[10],"methods":[11],"have":[12],"achieved":[13],"high":[14],"performance.":[15],"However,":[16],"it":[17],"is":[18,108,125],"hard":[19],"to":[20,64,69,86,92,110,114,127],"manually":[21],"label":[22,165],"edges":[23,144],"accurately,":[24],"especially":[25],"for":[26,44,50,58,132,142],"large":[27,140],"datasets,":[28],"and":[29,152],"thus":[30],"the":[31,55,71,88,100,112,143,155,162],"datasets":[32],"inevitably":[33],"contain":[34],"noisy":[35,93],"labels.":[36,116],"This":[37,136],"label-noise":[38,56],"issue":[39,57],"has":[40],"been":[41],"studied":[42],"extensively":[43],"classification,":[45],"while":[46],"still":[47],"remaining":[48],"under-explored":[49],"detection.":[52],"To":[53,74],"address":[54],"detection,":[60],"this":[61],"paper":[62],"proposes":[63],"learn":[65],"Pixel-level":[66],"Noise":[67],"Transitions":[68],"model":[70],"label-corruption":[72],"process.":[73],"achieve":[75],"it,":[76],"we":[77],"develop":[78],"a":[79,96,119],"novel":[80],"Pixel-wise":[81],"Shift":[82],"Learning":[83],"(PSL)":[84],"module":[85],"estimate":[87],"transition":[89,134],"from":[90],"clean":[91,115],"labels":[94],"as":[95],"displacement":[97],"field.":[98],"Exploiting":[99],"estimated":[101],"noise":[102],"transitions,":[103],"our":[104,158],"model,":[105],"named":[106],"PNT-Edge,":[107],"able":[109],"fit":[111],"prediction":[113],"In":[117],"addition,":[118],"local":[120,129,147],"density":[122],"regularization":[123],"term":[124,137],"devised":[126],"exploit":[128],"structure":[130],"information":[131],"better":[133],"learning.":[135],"encourages":[138],"learning":[139],"shifts":[141],"complex":[146],"structures.":[148],"Experiments":[149],"SBD":[151],"Cityscapes":[153],"demonstrate":[154],"effectiveness":[156],"of":[157,164],"method":[159],"in":[160],"relieving":[161],"impact":[163],"noise.":[166],"Codes":[167],"will":[168],"be":[169],"available":[170],"at":[171],"github.com/DREAMXFAR/PNT-Edge.":[172]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2023-07-28T00:00:00"}
