{"id":"https://openalex.org/W4405034364","doi":"https://doi.org/10.1109/iccv51701.2025.01173","title":"FoundIR: Unleashing Million-Scale Training Data to Advance Foundation Models for Image Restoration","display_name":"FoundIR: Unleashing Million-Scale Training Data to Advance Foundation Models for Image Restoration","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4405034364","doi":"https://doi.org/10.1109/iccv51701.2025.01173"},"language":"en","primary_location":{"id":"doi:10.1109/iccv51701.2025.01173","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.01173","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2412.01427","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100734156","display_name":"Zhengwei Li","orcid":"https://orcid.org/0000-0003-1644-1006"},"institutions":[{"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":"Hao Li","raw_affiliation_strings":["Nanjing University of Science and Technology,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology,China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011791240","display_name":"Xiang Chen","orcid":"https://orcid.org/0000-0002-0249-9664"},"institutions":[{"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":"Xiang Chen","raw_affiliation_strings":["Nanjing University of Science and Technology,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology,China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012044166","display_name":"Jiangxin Dong","orcid":"https://orcid.org/0000-0002-7529-9022"},"institutions":[{"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":"Jiangxin Dong","raw_affiliation_strings":["Nanjing University of Science and Technology,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology,China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035112538","display_name":"Jinhui Tang","orcid":"https://orcid.org/0000-0001-9008-222X"},"institutions":[{"id":"https://openalex.org/I167027274","display_name":"Nanjing Forestry University","ror":"https://ror.org/03m96p165","country_code":"CN","type":"education","lineage":["https://openalex.org/I167027274"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinhui Tang","raw_affiliation_strings":["Nanjing Forestry University,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing Forestry University,China","institution_ids":["https://openalex.org/I167027274"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004164569","display_name":"Jinshan Pan","orcid":"https://orcid.org/0000-0003-0304-9507"},"institutions":[{"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":"Jinshan Pan","raw_affiliation_strings":["Nanjing University of Science and Technology,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology,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":null,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"12626","last_page":"12636"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13067","display_name":"Geological Modeling and Analysis","score":0.9272000193595886,"subfield":{"id":"https://openalex.org/subfields/1906","display_name":"Geochemistry and Petrology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13067","display_name":"Geological Modeling and Analysis","score":0.9272000193595886,"subfield":{"id":"https://openalex.org/subfields/1906","display_name":"Geochemistry and Petrology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/foundation","display_name":"Foundation (evidence)","score":0.7247432470321655},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.6604361534118652},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.6015498638153076},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4771710932254791},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.4445699453353882},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4324291944503784},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3624725341796875},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.23772484064102173},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.23365187644958496},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.2009029984474182},{"id":"https://openalex.org/keywords/archaeology","display_name":"Archaeology","score":0.1086651086807251},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.06932616233825684}],"concepts":[{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.7247432470321655},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.6604361534118652},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.6015498638153076},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4771710932254791},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.4445699453353882},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4324291944503784},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3624725341796875},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.23772484064102173},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.23365187644958496},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2009029984474182},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.1086651086807251},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.06932616233825684}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iccv51701.2025.01173","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.01173","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2412.01427","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2412.01427","pdf_url":"https://arxiv.org/pdf/2412.01427","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":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2412.01427","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2412.01427","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2412.01427","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2412.01427","pdf_url":"https://arxiv.org/pdf/2412.01427","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":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5788325978","display_name":null,"funder_award_id":"U22B2049,62272233,62332010","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":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4405034364.pdf","grobid_xml":"https://content.openalex.org/works/W4405034364.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2381393187","https://openalex.org/W2332779545","https://openalex.org/W230091440","https://openalex.org/W2233261550","https://openalex.org/W2358060160","https://openalex.org/W2035483685","https://openalex.org/W2810751659","https://openalex.org/W2974904990","https://openalex.org/W2365681766","https://openalex.org/W2393963626"],"abstract_inverted_index":{"Despite":[0],"the":[1,45,152,172,192,198],"significant":[2],"progress":[3],"made":[4],"by":[5,150],"all-in-one":[6],"models":[7,49,183],"in":[8,19,61,129,176],"universal":[9],"image":[10,51,97],"restoration,":[11],"existing":[12,71],"methods":[13],"suffer":[14],"from":[15,156],"a":[16,63,116,123,133,143],"generalization":[17],"bottleneck":[18],"real-world":[20,37,74,130],"scenarios,":[21,131,178],"as":[22],"they":[23],"are":[24],"mostly":[25],"trained":[26],"on":[27],"small-scale":[28],"synthetic":[29],"datasets":[30],"with":[31,66,76,81],"limited":[32],"degradations.":[33],"Therefore,":[34],"large-scale":[35],"high-quality":[36,187],"training":[38,72],"data":[39,102,110],"is":[40,163],"urgently":[41],"needed":[42],"to":[43,120,147,165],"facilitate":[44],"emergence":[46],"of":[47,126,194,200],"foundational":[48],"for":[50,184],"restoration.":[52],"To":[53,170],"advance":[54],"this":[55],"field,":[56],"we":[57,93,114,140,179],"spare":[58],"no":[59],"effort":[60],"contributing":[62],"million-scale":[64],"dataset":[65,196],"two":[67],"notable":[68],"advantages":[69],"over":[70,105],"data:":[73],"samples":[75],"larger-scale,":[77],"and":[78,89,108,197],"degradation":[79],"types":[80],"higher":[82],"diversity.":[83],"By":[84],"adjusting":[85],"internal":[86],"camera":[87],"settings":[88],"external":[90],"imaging":[91],"conditions,":[92],"can":[94],"capture":[95],"aligned":[96],"pairs":[98],"using":[99],"our":[100,109,195,201],"well-designed":[101],"acquisition":[103],"system":[104],"multiple":[106],"rounds":[107],"alignment":[111],"criterion.":[112],"Moreover,":[113],"propose":[115],"robust":[117],"model,":[118],"FoundIR,":[119],"better":[121,166],"address":[122],"broader":[124],"range":[125],"restoration":[127,174],"tasks":[128],"taking":[132],"further":[134],"step":[135],"toward":[136],"foundation":[137],"models.":[138],"Specifically,":[139],"first":[141],"utilize":[142],"diffusion-based":[144],"generalist":[145],"model":[146,168],"remove":[148],"degradations":[149],"learning":[151,161],"degradation-agnostic":[153],"common":[154],"representations":[155],"diverse":[157],"inputs,":[158],"where":[159],"incremental":[160],"strategy":[162],"adopted":[164],"guide":[167],"training.":[169],"refine":[171],"model's":[173],"capability":[175],"complex":[177],"introduce":[180],"degradation-aware":[181],"specialist":[182],"achieving":[185],"final":[186],"results.":[188],"Extensive":[189],"experiments":[190],"show":[191],"value":[193],"effectiveness":[199],"method.":[202]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2024-12-05T00:00:00"}
