{"id":"https://openalex.org/W2949807960","doi":"https://doi.org/10.1109/tip.2020.2994413","title":"Integrating Neural Networks Into the Blind Deblurring Framework to Compete With the End-to-End Learning-Based Methods","display_name":"Integrating Neural Networks Into the Blind Deblurring Framework to Compete With the End-to-End Learning-Based Methods","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W2949807960","doi":"https://doi.org/10.1109/tip.2020.2994413","mag":"2949807960"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2020.2994413","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2020.2994413","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1903.02731","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Junde Wu","orcid":"https://orcid.org/0000-0002-1854-4773"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Junde Wu","raw_affiliation_strings":["Control and Simulation Center, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"Control and Simulation Center, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":null,"display_name":"Xiaoguang Di","orcid":"https://orcid.org/0000-0002-5709-6862"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoguang Di","raw_affiliation_strings":["Control and Simulation Center, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"Control and Simulation Center, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I204983213"],"apc_list":null,"apc_paid":null,"fwci":1.1777,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.80665163,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"29","issue":null,"first_page":"6841","last_page":"6851"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9261000156402588,"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":0.9261000156402588,"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":0.04910000041127205,"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":0.006200000178068876,"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":0.9710999727249146},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.609499990940094},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.5849999785423279},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5461000204086304},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5278000235557556},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5008000135421753},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.492000013589859},{"id":"https://openalex.org/keywords/motion-estimation","display_name":"Motion estimation","score":0.47110000252723694},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4377000033855438}],"concepts":[{"id":"https://openalex.org/C2777693668","wikidata":"https://www.wikidata.org/wiki/Q25053743","display_name":"Deblurring","level":5,"score":0.9710999727249146},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7684999704360962},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7129999995231628},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.609499990940094},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.5849999785423279},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5601000189781189},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5461000204086304},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5278000235557556},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5008000135421753},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.492000013589859},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.47110000252723694},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4377000033855438},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.39070001244544983},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.37310001254081726},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.36899998784065247},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.34869998693466187},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.32010000944137573},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.31459999084472656},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.30869999527931213},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.29260000586509705},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.28200000524520874},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.2815000116825104},{"id":"https://openalex.org/C72560505","wikidata":"https://www.wikidata.org/wiki/Q204510","display_name":"Motion interpolation","level":5,"score":0.26420000195503235},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2020.2994413","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2020.2994413","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1903.02731","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1903.02731","pdf_url":"https://arxiv.org/pdf/1903.02731","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:1903.02731","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1903.02731","pdf_url":"https://arxiv.org/pdf/1903.02731","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/G6065554584","display_name":null,"funder_award_id":"61775048","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1457323852","https://openalex.org/W1604428010","https://openalex.org/W1916935112","https://openalex.org/W1973567017","https://openalex.org/W1987075379","https://openalex.org/W1992309968","https://openalex.org/W2037642501","https://openalex.org/W2098535678","https://openalex.org/W2103913786","https://openalex.org/W2145339207","https://openalex.org/W2167307343","https://openalex.org/W2294215176","https://openalex.org/W2296055064","https://openalex.org/W2474628748","https://openalex.org/W2552111036","https://openalex.org/W2560533888","https://openalex.org/W2564023417","https://openalex.org/W2586480386","https://openalex.org/W2604469346","https://openalex.org/W2613155248","https://openalex.org/W2777194773","https://openalex.org/W2784344583","https://openalex.org/W2963073614","https://openalex.org/W2963130865","https://openalex.org/W2963312584","https://openalex.org/W2964030969","https://openalex.org/W2964040059","https://openalex.org/W6639102338","https://openalex.org/W6678815747","https://openalex.org/W6697925102","https://openalex.org/W6702130928","https://openalex.org/W6729858428","https://openalex.org/W6735857669","https://openalex.org/W6740801417","https://openalex.org/W6779669310"],"related_works":[],"abstract_inverted_index":{"Recently,":[0],"the":[1,10,83,97,102,106,111],"end-to-end":[2,108],"learning-based":[3,109],"methods":[4,37],"have":[5],"been":[6],"proven":[7],"effective":[8],"for":[9,101],"blind":[11],"image":[12,99,115],"deblurring.":[13],"Without":[14],"human-made":[15],"assumptions":[16],"or":[17],"numerical":[18],"algorithms,":[19],"they":[20],"are":[21],"able":[22],"to":[23,56,62,81,95],"restore":[24],"images":[25],"with":[26,105],"fewer":[27],"artifacts":[28],"and":[29,46,87,91,119],"better":[30,121],"perceptual":[31],"quality.":[32],"However,":[33],"in":[34,54],"practice,":[35],"these":[36],"suffer":[38],"from":[39],"limited":[40],"performance":[41],"under":[42],"complex":[43],"motion":[44,84],"scenario":[45],"produces":[47],"unnatural":[48],"results":[49],"sometimes.":[50],"In":[51],"this":[52],"paper,":[53],"order":[55],"overcome":[57],"their":[58],"limitations,":[59],"we":[60,74],"propose":[61,75],"integrate":[63],"deep":[64],"convolution":[65],"neural":[66],"networks":[67],"into":[68],"a":[69],"conventional":[70],"deblurring":[71],"framework.":[72],"Specifically,":[73],"Stacked":[76],"Estimation":[77],"Residual":[78],"Net":[79,93],"(SEN)":[80],"estimate":[82],"flow":[85],"map":[86],"Recurrent":[88],"Prior":[89],"Generative":[90],"Adversarial":[92],"(RP-GAN)":[94],"learn":[96],"implicit":[98],"prior":[100],"optimization.":[103],"Comparing":[104],"state-of-the-art":[107],"methods,":[110],"proposed":[112],"method":[113],"restores":[114],"content":[116],"more":[117],"naturally":[118],"shows":[120],"generalization":[122],"ability.":[123]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":2}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2019-06-27T00:00:00"}