{"id":"https://openalex.org/W4306814794","doi":"https://doi.org/10.48550/arxiv.2210.08036","title":"Meta Transferring for Deblurring","display_name":"Meta Transferring for Deblurring","publication_year":2022,"publication_date":"2022-10-14","ids":{"openalex":"https://openalex.org/W4306814794","doi":"https://doi.org/10.48550/arxiv.2210.08036"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2210.08036","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2210.08036","pdf_url":"https://arxiv.org/pdf/2210.08036","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2210.08036","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054798583","display_name":"Po-Sheng Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Po-Sheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008445060","display_name":"Fu-Jen Tsai","orcid":"https://orcid.org/0000-0003-1486-2229"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tsai, Fu-Jen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016386447","display_name":"Yan\u2010Tsung Peng","orcid":"https://orcid.org/0000-0002-3802-1670"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peng, Yan-Tsung","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035164036","display_name":"Chung-Chi Tsai","orcid":"https://orcid.org/0000-0003-1792-9978"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tsai, Chung-Chi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051264473","display_name":"Chia\u2010Wen Lin","orcid":"https://orcid.org/0000-0002-9097-2318"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Chia-Wen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5002217153","display_name":"Yen\u2010Yu Lin","orcid":"https://orcid.org/0000-0002-7183-6070"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Yen-Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9991000294685364,"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":0.9991000294685364,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9789999723434448,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9509000182151794,"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":0.9960801601409912},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6836641430854797},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.6769038438796997},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6613034605979919},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6230425238609314},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5555941462516785},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5468409657478333},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5294473171234131},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.461392879486084},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4216911196708679},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.39959198236465454},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.21143540740013123},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18978604674339294},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.09294295310974121}],"concepts":[{"id":"https://openalex.org/C2777693668","wikidata":"https://www.wikidata.org/wiki/Q25053743","display_name":"Deblurring","level":5,"score":0.9960801601409912},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6836641430854797},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.6769038438796997},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6613034605979919},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6230425238609314},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5555941462516785},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5468409657478333},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5294473171234131},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.461392879486084},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4216911196708679},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.39959198236465454},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.21143540740013123},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18978604674339294},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.09294295310974121},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2210.08036","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2210.08036","pdf_url":"https://arxiv.org/pdf/2210.08036","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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"},{"id":"doi:10.48550/arxiv.2210.08036","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2210.08036","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2210.08036","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2210.08036","pdf_url":"https://arxiv.org/pdf/2210.08036","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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/G1944809431","display_name":null,"funder_award_id":"110-2634-F-006-022","funder_id":"https://openalex.org/F4320331164","funder_display_name":"National Science and Technology Council"},{"id":"https://openalex.org/G2452754452","display_name":null,"funder_award_id":"111-2628-E-A49-025-MY3","funder_id":"https://openalex.org/F4320331164","funder_display_name":"National Science and Technology Council"},{"id":"https://openalex.org/G7139107657","display_name":null,"funder_award_id":"110-2634-F-002-050","funder_id":"https://openalex.org/F4320331164","funder_display_name":"National Science and Technology Council"},{"id":"https://openalex.org/G8290191761","display_name":null,"funder_award_id":"111-2221-E-004-010","funder_id":"https://openalex.org/F4320331164","funder_display_name":"National Science and Technology Council"}],"funders":[{"id":"https://openalex.org/F4320316499","display_name":"National Applied Research Laboratories","ror":"https://ror.org/05wcstg80"},{"id":"https://openalex.org/F4320322410","display_name":"MediaTek","ror":"https://ror.org/05g9jck81"},{"id":"https://openalex.org/F4320331164","display_name":"National Science and Technology Council","ror":"https://ror.org/00wnb9798"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2031788393","https://openalex.org/W791927757","https://openalex.org/W2182590612","https://openalex.org/W2905397092","https://openalex.org/W3034770329","https://openalex.org/W2089488370","https://openalex.org/W3153582293","https://openalex.org/W4220831754","https://openalex.org/W3207832039","https://openalex.org/W2269775642"],"abstract_inverted_index":{"Most":[0],"previous":[1],"deblurring":[2,24,138],"methods":[3],"were":[4],"built":[5],"with":[6,120],"a":[7,40,67,91,122],"generic":[8],"model":[9,93],"trained":[10],"on":[11,140],"blurred":[12,73,101],"images":[13],"and":[14,34,78,103,117,144],"their":[15],"sharp":[16,81],"counterparts.":[17],"However,":[18],"these":[19],"approaches":[20],"might":[21],"have":[22],"sub-optimal":[23],"results":[25,128],"due":[26],"to":[27,44,76,94,106,109],"the":[28,32,57,72,84,96,100,107,111,141],"domain":[29],"gap":[30],"between":[31],"training":[33],"test":[35],"sets.":[36],"This":[37],"paper":[38],"proposes":[39],"reblur-deblur":[41,132],"meta-transferring":[42],"scheme":[43,134],"realize":[45],"test-time":[46,118],"adaptation":[47,119],"without":[48],"using":[49],"ground":[50,58,86],"truth":[51,59],"for":[52,115],"dynamic":[53],"scene":[54],"deblurring.":[55],"Since":[56],"is":[60],"usually":[61],"unavailable":[62],"at":[63],"inference":[64],"time":[65],"in":[66],"real-world":[68],"scenario,":[69],"we":[70,89],"leverage":[71],"input":[74,102],"video":[75],"find":[77],"use":[79],"relatively":[80],"patches":[82,114],"as":[83],"pseudo":[85],"truth.":[87],"Furthermore,":[88],"propose":[90],"reblurring":[92],"extract":[95],"homogenous":[97],"blur":[98],"from":[99],"transfer":[104],"it":[105],"pseudo-sharps":[108],"obtain":[110],"corresponding":[112],"pseudo-blurred":[113],"meta-learning":[116,133],"only":[121],"few":[123],"gradient":[124],"updates.":[125],"Extensive":[126],"experimental":[127],"show":[129],"that":[130],"our":[131],"can":[135],"improve":[136],"state-of-the-art":[137],"models":[139],"DVD,":[142],"REDS,":[143],"RealBlur":[145],"benchmark":[146],"datasets.":[147]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2025-10-10T00:00:00"}