{"id":"https://openalex.org/W2958533088","doi":"https://doi.org/10.1109/lsp.2019.2939752","title":"Edge Heuristic GAN for Non-Uniform Blind Deblurring","display_name":"Edge Heuristic GAN for Non-Uniform Blind Deblurring","publication_year":2019,"publication_date":"2019-09-05","ids":{"openalex":"https://openalex.org/W2958533088","doi":"https://doi.org/10.1109/lsp.2019.2939752","mag":"2958533088"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2019.2939752","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2019.2939752","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Signal Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1907.05185","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Shuai Zheng","orcid":"https://orcid.org/0000-0001-8560-8135"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Zheng","raw_affiliation_strings":["Institute of Information Science, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8560-8135","affiliations":[{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhenfeng Zhu","orcid":"https://orcid.org/0000-0001-7315-3276"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenfeng Zhu","raw_affiliation_strings":["Institute of Information Science, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7315-3276","affiliations":[{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jian Cheng","orcid":"https://orcid.org/0000-0003-1289-2758"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"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":"Jian Cheng","raw_affiliation_strings":["National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences and University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-1289-2758","affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences and University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yandong Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yandong Guo","raw_affiliation_strings":["Xpeng Motors, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xpeng Motors, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":null,"display_name":"Yao Zhao","orcid":"https://orcid.org/0000-0002-8581-9554"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Zhao","raw_affiliation_strings":["Institute of Information Science, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-8581-9554","affiliations":[{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.5806,"has_fulltext":false,"cited_by_count":39,"citation_normalized_percentile":{"value":0.92044088,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"26","issue":"10","first_page":"1546","last_page":"1550"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9926000237464905,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9926000237464905,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.0032999999821186066,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.002099999925121665,"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/deblurring","display_name":"Deblurring","score":0.994700014591217},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.7026000022888184},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.6288999915122986},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.6065000295639038},{"id":"https://openalex.org/keywords/motion-blur","display_name":"Motion blur","score":0.5963000059127808},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5390999913215637},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4514999985694885},{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"Kernel density estimation","score":0.4115999937057495}],"concepts":[{"id":"https://openalex.org/C2777693668","wikidata":"https://www.wikidata.org/wiki/Q25053743","display_name":"Deblurring","level":5,"score":0.994700014591217},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7074999809265137},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.7026000022888184},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7023000121116638},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.6288999915122986},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.6065000295639038},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6050999760627747},{"id":"https://openalex.org/C2777708103","wikidata":"https://www.wikidata.org/wiki/Q852589","display_name":"Motion blur","level":3,"score":0.5963000059127808},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5390999913215637},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4514999985694885},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.4115999937057495},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.396699994802475},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.39089998602867126},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.3287999927997589},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3142000138759613},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.29649999737739563},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.2953999936580658},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.2648000121116638},{"id":"https://openalex.org/C11727466","wikidata":"https://www.wikidata.org/wiki/Q1628157","display_name":"Inpainting","level":3,"score":0.26190000772476196},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.2590000033378601},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2565000057220459}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lsp.2019.2939752","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2019.2939752","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Signal Processing Letters","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1907.05185","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1907.05185","pdf_url":"https://arxiv.org/pdf/1907.05185","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:1907.05185","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1907.05185","pdf_url":"https://arxiv.org/pdf/1907.05185","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":[],"awards":[{"id":"https://openalex.org/G3224329043","display_name":null,"funder_award_id":"2019YJS048","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G43915001","display_name":"\u591a\u89c6\u89d2\u5b66\u4e60\u7406\u8bba\u4e0e\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61572068","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7072385062","display_name":null,"funder_award_id":"61532005","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8703986653","display_name":null,"funder_award_id":"2019JBM018","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1457323852","https://openalex.org/W1604428010","https://openalex.org/W1916935112","https://openalex.org/W1987075379","https://openalex.org/W2036682493","https://openalex.org/W2098535678","https://openalex.org/W2103913786","https://openalex.org/W2133957619","https://openalex.org/W2138204001","https://openalex.org/W2166694921","https://openalex.org/W2167307343","https://openalex.org/W2194775991","https://openalex.org/W2474628748","https://openalex.org/W2476548250","https://openalex.org/W2560533888","https://openalex.org/W2604469346","https://openalex.org/W2738579427","https://openalex.org/W2738588019","https://openalex.org/W2962793481","https://openalex.org/W2963073614","https://openalex.org/W2963130865","https://openalex.org/W2963312584","https://openalex.org/W2963446712","https://openalex.org/W2963470893","https://openalex.org/W2963800363","https://openalex.org/W2963996760","https://openalex.org/W2964116203","https://openalex.org/W6637568146","https://openalex.org/W6639824700","https://openalex.org/W6678856934","https://openalex.org/W6702130928","https://openalex.org/W6724804524","https://openalex.org/W6735913928","https://openalex.org/W6744107740","https://openalex.org/W6765562228","https://openalex.org/W6766878880","https://openalex.org/W6779669310"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2600744954","https://openalex.org/W2374403394","https://openalex.org/W3201406873","https://openalex.org/W1987894726","https://openalex.org/W2953655861","https://openalex.org/W4291270817","https://openalex.org/W3094601080","https://openalex.org/W3202921169"],"abstract_inverted_index":{"Non-uniform":[0],"blur,":[1],"mainly":[2],"caused":[3],"by":[4],"camera":[5],"shake":[6],"and":[7],"motions":[8],"of":[9,14,19,64],"multiple":[10],"objects,":[11],"is":[12,98],"one":[13],"the":[15,24,62,82,109],"most":[16],"common":[17],"causes":[18],"image":[20],"quality":[21],"degradation.":[22],"However,":[23,43],"traditional":[25],"blind":[26],"deblurring":[27,54,68,110,121],"methods":[28,66],"based":[29],"on":[30,38,53,67,125],"blur":[31],"kernel":[32],"estimation":[33],"do":[34],"not":[35],"perform":[36],"well":[37],"complicated":[39],"non-uniform":[40],"motion":[41],"blurs.":[42],"recent":[44],"studies":[45],"show":[46,128],"that":[47,129],"GAN-based":[48,65],"approaches":[49],"achieve":[50],"impressive":[51],"performance":[52,63,134],"tasks.":[55,122],"In":[56,93],"this":[57],"letter,":[58],"to":[59,85,100,107],"further":[60],"improve":[61],"tasks,":[69],"we":[70],"propose":[71,114],"an":[72,90,95],"edge":[73],"heuristic":[74],"multi-scale":[75],"generative":[76],"adversarial":[77],"network":[78,97],"(GAN),":[79],"which":[80],"uses":[81],"coarse-to-fine":[83],"scheme":[84],"restore":[86],"clear":[87],"images":[88],"in":[89,135],"end-to-end":[91],"manner.":[92],"particular,":[94],"edge-generated":[96],"designed":[99],"generate":[101],"sharp":[102],"edges":[103],"as":[104],"auxiliary":[105],"information":[106],"guide":[108],"process.":[111],"Furthermore,":[112],"We":[113],"a":[115],"hierarchical":[116],"content":[117],"loss":[118],"function":[119],"for":[120],"Extensive":[123],"experiments":[124],"different":[126],"datasets":[127],"our":[130],"method":[131],"achieves":[132],"state-of-the-art":[133],"dynamic":[136],"scene":[137],"deblurring.":[138]},"counts_by_year":[{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2019-07-23T00:00:00"}