{"id":"https://openalex.org/W4390872583","doi":"https://doi.org/10.1109/iccv51070.2023.01204","title":"DiffIR: Efficient Diffusion Model for Image Restoration","display_name":"DiffIR: Efficient Diffusion Model for Image Restoration","publication_year":2023,"publication_date":"2023-10-01","ids":{"openalex":"https://openalex.org/W4390872583","doi":"https://doi.org/10.1109/iccv51070.2023.01204"},"language":"en","primary_location":{"id":"doi:10.1109/iccv51070.2023.01204","doi":"https://doi.org/10.1109/iccv51070.2023.01204","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51070.2023.01204","pdf_url":null,"source":{"id":"https://openalex.org/S4363607764","display_name":"IEEE/CVF International Conference on Computer Vision (ICCV)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2303.09472","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100751857","display_name":"Bin Xia","orcid":"https://orcid.org/0000-0002-5583-3275","observed_orcids":["https://orcid.org/0000-0002-5583-3275"]},"institutions":[{"id":"https://openalex.org/I4405256866","display_name":"ByteDance (China)","ror":"https://ror.org/04m8av638","country_code":"CN","type":"company","lineage":["https://openalex.org/I4405256866"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Xia","raw_affiliation_strings":["Tsinghua University","ByteDance Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"ByteDance Inc","institution_ids":["https://openalex.org/I4405256866"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074865219","display_name":"Yulun Zhang","orcid":"https://orcid.org/0000-0002-2288-5079","observed_orcids":["https://orcid.org/0000-0002-2288-5079"]},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Yulun Zhang","raw_affiliation_strings":["ETH Z\u00fcrich"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ETH Z\u00fcrich","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114514359","display_name":"Shiyin Wang","orcid":"https://orcid.org/0009-0004-7206-4975","observed_orcids":["https://orcid.org/0009-0004-7206-4975"]},"institutions":[{"id":"https://openalex.org/I4405256866","display_name":"ByteDance (China)","ror":"https://ror.org/04m8av638","country_code":"CN","type":"company","lineage":["https://openalex.org/I4405256866"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiyin Wang","raw_affiliation_strings":["ByteDance Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ByteDance Inc","institution_ids":["https://openalex.org/I4405256866"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100650009","display_name":"Yitong Wang","orcid":"https://orcid.org/0000-0002-7559-4152","observed_orcids":["https://orcid.org/0000-0002-7559-4152"]},"institutions":[{"id":"https://openalex.org/I4405256866","display_name":"ByteDance (China)","ror":"https://ror.org/04m8av638","country_code":"CN","type":"company","lineage":["https://openalex.org/I4405256866"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yitong Wang","raw_affiliation_strings":["ByteDance Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ByteDance Inc","institution_ids":["https://openalex.org/I4405256866"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xinglong Wu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405256866","display_name":"ByteDance (China)","ror":"https://ror.org/04m8av638","country_code":"CN","type":"company","lineage":["https://openalex.org/I4405256866"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinglong Wu","raw_affiliation_strings":["ByteDance Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ByteDance Inc","institution_ids":["https://openalex.org/I4405256866"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101835756","display_name":"Yapeng Tian","orcid":"https://orcid.org/0000-0003-1423-4513","observed_orcids":["https://orcid.org/0000-0003-1423-4513"]},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yapeng Tian","raw_affiliation_strings":["University of Texas at Dallas"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Texas at Dallas","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017958896","display_name":"Wenming Yang","orcid":"https://orcid.org/0000-0002-9277-1827","observed_orcids":["https://orcid.org/0000-0002-9277-1827"]},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenming Yang","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001254143","display_name":"Luc Van Gool","orcid":"https://orcid.org/0000-0002-3445-5711","observed_orcids":["https://orcid.org/0000-0002-3445-5711"]},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Luc Van Gool","raw_affiliation_strings":["ETH Z\u00fcrich"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ETH Z\u00fcrich","institution_ids":["https://openalex.org/I35440088"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":41.9459,"has_fulltext":true,"cited_by_count":477,"citation_normalized_percentile":{"value":0.99818562,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"13049","last_page":"13059"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.43380001187324524,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.43380001187324524,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.4302000105381012,"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":0.10679999738931656,"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/image-restoration","display_name":"image restoration","score":0.8450000286102295},{"id":"https://openalex.org/keywords/diffusion-models","display_name":"diffusion models","score":0.9580000042915344},{"id":"https://openalex.org/keywords/pretraining","display_name":"pre-training","score":0.5339999794960022},{"id":"https://openalex.org/keywords/low-quality-images","display_name":"low-quality images","score":0.7039999961853027},{"id":"https://openalex.org/keywords/computational-efficiency","display_name":"computational efficiency","score":0.6140000224113464},{"id":"https://openalex.org/keywords/joint-optimization","display_name":"joint optimization","score":0.7070000171661377}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6198340654373169},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5495360493659973},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.4934214651584625},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4872792959213257},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.47950202226638794},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.42070281505584717},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34431469440460205},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18355804681777954},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iccv51070.2023.01204","doi":"https://doi.org/10.1109/iccv51070.2023.01204","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51070.2023.01204","pdf_url":null,"source":{"id":"https://openalex.org/S4363607764","display_name":"IEEE/CVF International Conference on Computer Vision (ICCV)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2303.09472","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2303.09472","pdf_url":"https://arxiv.org/pdf/2303.09472","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,"listed_in":[],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2303.09472","doi":"https://doi.org/10.48550/arxiv.2303.09472","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2303.09472","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,"listed_in":[],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2303.09472","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2303.09472","pdf_url":"https://arxiv.org/pdf/2303.09472","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,"listed_in":[],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4390872583.pdf","grobid_xml":"https://content.openalex.org/works/W4390872583.grobid-xml"},"referenced_works_count":72,"referenced_works":["https://openalex.org/W1791560514","https://openalex.org/W1885185971","https://openalex.org/W1930824406","https://openalex.org/W2047920195","https://openalex.org/W2125389028","https://openalex.org/W2142683286","https://openalex.org/W2167307343","https://openalex.org/W2192954843","https://openalex.org/W2242218935","https://openalex.org/W2342877626","https://openalex.org/W2503339013","https://openalex.org/W2508457857","https://openalex.org/W2557216475","https://openalex.org/W2560533888","https://openalex.org/W2605135824","https://openalex.org/W2732026016","https://openalex.org/W2739757502","https://openalex.org/W2741137940","https://openalex.org/W2766527293","https://openalex.org/W2768546798","https://openalex.org/W2798735168","https://openalex.org/W2807633959","https://openalex.org/W2866634454","https://openalex.org/W2907097116","https://openalex.org/W2919720707","https://openalex.org/W2954930822","https://openalex.org/W2961218591","https://openalex.org/W2962785568","https://openalex.org/W2962935103","https://openalex.org/W2963470893","https://openalex.org/W2963814095","https://openalex.org/W2964030969","https://openalex.org/W2965217508","https://openalex.org/W2982795046","https://openalex.org/W2985764327","https://openalex.org/W2986532955","https://openalex.org/W2987869089","https://openalex.org/W2988641380","https://openalex.org/W3012811655","https://openalex.org/W3030520226","https://openalex.org/W3034419329","https://openalex.org/W3034789174","https://openalex.org/W3035484352","https://openalex.org/W3035557850","https://openalex.org/W3037932933","https://openalex.org/W3043547428","https://openalex.org/W3081639259","https://openalex.org/W3092462694","https://openalex.org/W3131500599","https://openalex.org/W3134449767","https://openalex.org/W3136958399","https://openalex.org/W3137506875","https://openalex.org/W3144276858","https://openalex.org/W3147328569","https://openalex.org/W3155072588","https://openalex.org/W3164815015","https://openalex.org/W3170697543","https://openalex.org/W3170841864","https://openalex.org/W3171125843","https://openalex.org/W3199003182","https://openalex.org/W3202040256","https://openalex.org/W3207918547","https://openalex.org/W3212516020","https://openalex.org/W4200633475","https://openalex.org/W4221147148","https://openalex.org/W4225672218","https://openalex.org/W4226014430","https://openalex.org/W4312383858","https://openalex.org/W4312497550","https://openalex.org/W4312933868","https://openalex.org/W4312938066","https://openalex.org/W7133213775"],"related_works":["https://openalex.org/W4385804996","https://openalex.org/W4413794661","https://openalex.org/W4411469128","https://openalex.org/W4415798075","https://openalex.org/W7171386902","https://openalex.org/W4404184225","https://openalex.org/W4400945200","https://openalex.org/W4413144894","https://openalex.org/W4392237630","https://openalex.org/W4391462741"],"abstract_inverted_index":{"Diffusion":[0],"model":[1,51],"(DM)":[2],"has":[3,29,92],"achieved":[4],"SOTA":[5,204],"performance":[6,205],"by":[7],"modeling":[8],"the":[9,119,124,129,142,169,190],"image":[10,24,26],"synthesis":[11],"process":[12],"into":[13,106],"a":[14,18,30,49,76,109,146,177],"sequential":[15],"application":[16],"of":[17,75,180],"denoising":[19,88,184],"network.":[20,89],"However,":[21],"different":[22],"from":[23],"synthesis,":[25],"restoration":[27],"(IR)":[28],"strong":[31],"constraint":[32],"to":[33,52,115,126,157],"generate":[34,162],"results":[35],"in":[36],"accordance":[37],"with":[38],"ground-truth.":[39],"Thus,":[40],"for":[41,70],"IR,":[42],"traditional":[43,155],"DMs":[44],"running":[45],"massive":[46],"iterations":[47,153,170],"on":[48,198],"large":[50],"estimate":[53,128],"whole":[54],"images":[55,105],"or":[56],"feature":[57],"maps":[58],"is":[59,144,212],"inefficient.":[60],"To":[61],"address":[62],"this":[63],"issue,":[64],"we":[65,102,122],"propose":[66],"an":[67],"efficient":[68],"DM":[69,125,156],"IR":[71,78,84,111,200],"(DiffIR),":[72],"which":[73,186],"consists":[74],"compact":[77,110,147],"prior":[79,112],"extraction":[80],"network":[81],"(CPEN),":[82],"dynamic":[83],"transformer":[85],"(DIRformer),":[86],"and":[87,97,161,165,183,202],"Specifically,":[90],"DiffIR":[91,149,174],"two":[93],"training":[94,98],"stages:":[95],"pretraining":[96],"DM.":[99],"In":[100,118],"pretraining,":[101],"input":[103],"ground-truth":[104],"CPENS1to":[107],"capture":[108],"representation":[113],"(IPR)":[114],"guide":[116],"DIRformer.":[117],"second":[120],"stage,":[121],"train":[123],"directly":[127],"same":[130],"IRP":[131],"as":[132],"pretrained":[133],"CPENS1only":[134],"using":[135],"LQ":[136],"images.":[137],"We":[138,194],"observe":[139],"that":[140],"since":[141],"IPR":[143],"only":[145],"vector,":[148],"can":[150,175,187],"use":[151],"fewer":[152],"than":[154],"obtain":[158],"accurate":[159],"estimations":[160],"more":[163],"stable":[164],"realistic":[166],"results.":[167],"Since":[168],"are":[171],"few,":[172],"our":[173],"adopt":[176],"joint":[178],"optimization":[179],"CPENS2,":[181],"DIRformer,":[182],"network,":[185],"further":[188],"reduce":[189],"estimation":[191],"error":[192],"influence.":[193],"conduct":[195],"extensive":[196],"experiments":[197],"several":[199],"tasks":[201],"achieve":[203],"while":[206],"consuming":[207],"less":[208],"computational":[209],"costs.":[210],"Code":[211],"available":[213],"at":[214],"https://github.com/Zj-BinXia/DiffIR.":[215]},"counts_by_year":[{"year":2026,"cited_by_count":147},{"year":2025,"cited_by_count":188},{"year":2024,"cited_by_count":132},{"year":2023,"cited_by_count":10}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2024-01-16T00:00:00"}