{"id":"https://openalex.org/W4378194948","doi":"https://doi.org/10.1109/tcsvt.2023.3279981","title":"Joint Learning of Image Deblurring and Depth Estimation Through Adversarial Multi-Task Network","display_name":"Joint Learning of Image Deblurring and Depth Estimation Through Adversarial Multi-Task Network","publication_year":2023,"publication_date":"2023-05-25","ids":{"openalex":"https://openalex.org/W4378194948","doi":"https://doi.org/10.1109/tcsvt.2023.3279981"},"language":"en","primary_location":{"id":"doi:10.1109/tcsvt.2023.3279981","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2023.3279981","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"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 Circuits and Systems for Video Technology","raw_type":"journal-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/A5052586758","display_name":"Shengyu Hou","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengyu Hou","raw_affiliation_strings":["School of Automation, Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091459774","display_name":"Mengyin Fu","orcid":"https://orcid.org/0000-0002-5520-7127"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengyin Fu","raw_affiliation_strings":["School of Automation, Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029808668","display_name":"Wenjie Song","orcid":"https://orcid.org/0000-0002-4121-908X"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]},{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjie Song","raw_affiliation_strings":["School of Automation, Beijing Institute of Technology, Beijing, China","School of Automation, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-4121-908X","affiliations":[{"raw_affiliation_string":"School of Automation, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"School of Automation, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9573,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.76860439,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"33","issue":"12","first_page":"7327","last_page":"7341"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/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"}}],"keywords":[{"id":"https://openalex.org/keywords/deblurring","display_name":"Deblurring","score":0.8973015546798706},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7483565807342529},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7428231239318848},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5405122637748718},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47948798537254333},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.41139790415763855},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.35669416189193726},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3053681254386902},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.2658575773239136},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.10524404048919678}],"concepts":[{"id":"https://openalex.org/C2777693668","wikidata":"https://www.wikidata.org/wiki/Q25053743","display_name":"Deblurring","level":5,"score":0.8973015546798706},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7483565807342529},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7428231239318848},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5405122637748718},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47948798537254333},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.41139790415763855},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.35669416189193726},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3053681254386902},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2658575773239136},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.10524404048919678}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsvt.2023.3279981","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2023.3279981","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"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 Circuits and Systems for Video Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2217668812","display_name":null,"funder_award_id":"61903034","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5448203614","display_name":null,"funder_award_id":"61973034","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7914619715","display_name":null,"funder_award_id":"U1913203","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":57,"referenced_works":["https://openalex.org/W78159342","https://openalex.org/W125693051","https://openalex.org/W1547225365","https://openalex.org/W1905829557","https://openalex.org/W1915250530","https://openalex.org/W2043236320","https://openalex.org/W2085431493","https://openalex.org/W2109030076","https://openalex.org/W2115579991","https://openalex.org/W2143668817","https://openalex.org/W2194775991","https://openalex.org/W2300779272","https://openalex.org/W2331128040","https://openalex.org/W2520707372","https://openalex.org/W2553576544","https://openalex.org/W2560533888","https://openalex.org/W2562137921","https://openalex.org/W2793286375","https://openalex.org/W2884585870","https://openalex.org/W2884886306","https://openalex.org/W2886668163","https://openalex.org/W2888531279","https://openalex.org/W2890474520","https://openalex.org/W2900331589","https://openalex.org/W2953823547","https://openalex.org/W2963073614","https://openalex.org/W2963257642","https://openalex.org/W2963312584","https://openalex.org/W2963498646","https://openalex.org/W2963583471","https://openalex.org/W2964030969","https://openalex.org/W2964251418","https://openalex.org/W2974383094","https://openalex.org/W2976842945","https://openalex.org/W2979600871","https://openalex.org/W2981353488","https://openalex.org/W2985775862","https://openalex.org/W2988641380","https://openalex.org/W2995689976","https://openalex.org/W3009153202","https://openalex.org/W3034604951","https://openalex.org/W3035434014","https://openalex.org/W3101202235","https://openalex.org/W3151841177","https://openalex.org/W3162552392","https://openalex.org/W3170697543","https://openalex.org/W3173274332","https://openalex.org/W3176096490","https://openalex.org/W3191659868","https://openalex.org/W3202040256","https://openalex.org/W3204559841","https://openalex.org/W4205172069","https://openalex.org/W4214815024","https://openalex.org/W4286373874","https://openalex.org/W4313185116","https://openalex.org/W6729809565","https://openalex.org/W6753801691"],"related_works":["https://openalex.org/W2031788393","https://openalex.org/W791927757","https://openalex.org/W2182590612","https://openalex.org/W2905397092","https://openalex.org/W3153582293","https://openalex.org/W2269775642","https://openalex.org/W3080537281","https://openalex.org/W2289746762","https://openalex.org/W2359633702","https://openalex.org/W2140617750"],"abstract_inverted_index":{"Self-supervised":[0],"monocular":[1],"depth":[2,23,49,69,184],"estimation":[3,50,70,185],"methods":[4],"have":[5],"achieved":[6],"remarkable":[7],"results":[8,182],"on":[9,132,164],"natural":[10],"clear":[11],"images.":[12],"However,":[13],"it":[14],"is":[15],"still":[16],"a":[17,42,80,105,147],"serious":[18],"challenge":[19],"to":[20,86,111,119,152],"directly":[21],"recover":[22],"information":[24],"from":[25,76],"blurred":[26],"images":[27],"caused":[28],"by":[29,100,136],"long-time":[30],"exposure":[31],"while":[32],"camera":[33],"fast":[34],"moving.":[35],"To":[36],"address":[37],"this":[38],"issue,":[39],"we":[40],"propose":[41],"unified":[43],"framework":[44,73],"for":[45,95,183],"simultaneous":[46],"deblurring":[47,66],"and":[48,57,68,130,172,186],"(SDDE),":[51],"which":[52],"has":[53],"higher":[54],"coupling":[55],"performance":[56],"flexibility":[58],"compared":[59],"with":[60],"the":[61,89,96,116,133,138,143,155],"simple":[62],"concatenation":[63],"strategy":[64],"of":[65,124,142],"model":[67],"model.":[71],"This":[72,160],"mainly":[74],"benefits":[75],"three":[77],"features:":[78],"1)":[79],"novel":[81],"Task-aware":[82],"Fusion":[83],"Module":[84,109],"(TFM)":[85],"adaptively":[87],"select":[88],"most":[90],"relevant":[91],"intermediate":[92],"shared":[93,156],"features":[94],"dual":[97],"decoder":[98,158],"network":[99],"aggregating":[101],"multi-scale":[102],"features,":[103],"2)":[104],"unique":[106],"Spatial":[107],"Interaction":[108],"(SIM)":[110],"learn":[112],"higher-order":[113],"representation":[114],"in":[115,127,180],"encoder":[117],"stage":[118],"better":[120],"describe":[121],"complex":[122],"boundaries":[123],"different":[125],"classes":[126],"high-dimensional":[128],"space,":[129],"focuses":[131],"task-related":[134],"region":[135],"modeling":[137],"pairwise":[139],"spatial":[140],"correlation":[141],"holistic":[144],"tensor,":[145],"3)":[146],"Priors-Based":[148],"Composite":[149],"Regularization":[150],"term":[151],"jointly":[153],"optimize":[154],"encoder-dual":[157],"network.":[159],"work":[161],"was":[162],"evaluated":[163],"multiple":[165],"datasets,":[166],"including:":[167],"Stereo":[168],"blur,":[169],"KITTI,NYUv2,":[170],"REDS":[171],"our":[173],"own":[174],"large-scale":[175],"stereo":[176],"blur":[177],"dataset,":[178],"resulting":[179],"state-of-the-art":[181],"image":[187],"deblurring,":[188],"respectively.":[189]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}