{"id":"https://openalex.org/W7163051152","doi":"https://doi.org/10.48550/arxiv.2605.30915","title":"DiTTo: Scalable Order-aware All-in-One Image Restoration Agent","display_name":"DiTTo: Scalable Order-aware All-in-One Image Restoration Agent","publication_year":2026,"publication_date":"2026-05-29","ids":{"openalex":"https://openalex.org/W7163051152","doi":"https://doi.org/10.48550/arxiv.2605.30915"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.30915","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30915","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":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.30915","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137607587","display_name":"Seungho Choi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Choi, Seungho","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5090121183","display_name":"Jihyong Oh","orcid":"https://orcid.org/0000-0002-1627-0529"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Oh, Jihyong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"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/T11019","display_name":"Image Enhancement Techniques","score":0.3702000081539154,"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/T11019","display_name":"Image Enhancement Techniques","score":0.3702000081539154,"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":0.2556999921798706,"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":0.24950000643730164,"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/scalability","display_name":"Scalability","score":0.6444000005722046},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5911999940872192},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5347999930381775},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.48590001463890076},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.47690001130104065},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.47589999437332153},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.4733000099658966}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6956999897956848},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6444000005722046},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5911999940872192},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5347999930381775},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.48590001463890076},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.47690001130104065},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.47589999437332153},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.4733000099658966},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4153999984264374},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3700999915599823},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.3695000112056732},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.36239999532699585},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.35269999504089355},{"id":"https://openalex.org/C2779679103","wikidata":"https://www.wikidata.org/wiki/Q5251805","display_name":"Degradation (telecommunications)","level":2,"score":0.34389999508857727},{"id":"https://openalex.org/C2778029271","wikidata":"https://www.wikidata.org/wiki/Q5421931","display_name":"Extension (predicate logic)","level":2,"score":0.33180001378059387},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.32199999690055847},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3154999911785126},{"id":"https://openalex.org/C32833848","wikidata":"https://www.wikidata.org/wiki/Q4115054","display_name":"Extensibility","level":2,"score":0.2757999897003174}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.30915","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30915","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.30915","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30915","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":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.685400664806366}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Real-world":[0],"images":[1],"rarely":[2],"suffer":[3],"from":[4],"a":[5,28,32,72,95,169],"single":[6],"degradation,":[7],"and":[8,67,89,107,120,157],"the":[9,18,49,58,64,104,108,135,143,175,180],"order":[10],"in":[11,63],"which":[12],"degradations":[13],"are":[14],"removed":[15],"substantially":[16],"affects":[17],"final":[19],"restoration":[20,25,99,196],"quality,":[21],"motivating":[22],"agent-based":[23,200],"image":[24,46,98],"(IR),":[26],"where":[27,55],"vision-language":[29],"model":[30],"schedules":[31],"pool":[33],"of":[34,60,103],"pre-built":[35],"restoration-experts.":[36],"However,":[37],"existing":[38],"training-based":[39],"agents":[40],"require":[41],"$\\mathcal{O}((N^{\\mathbf{D}})^{2})$":[42],"restoration-expert":[43,74,171],"calls":[44,132],"per":[45,133],"to":[47,71,78,129,186],"construct":[48],"Optimal":[50],"Restoration-action":[51],"Trajectory":[52],"Dataset":[53],"(ORTD),":[54],"$N^{\\mathbf{D}}$":[56],"denotes":[57],"number":[59],"degradation":[61,154],"types":[62],"universe":[65],"$\\mathbf{D}$,":[66],"couple":[68],"agent":[69,100],"training":[70],"fixed":[73],"pool,":[75],"preventing":[76],"extension":[77],"newly":[79],"introduced":[80],"restoration-experts":[81],"without":[82],"full":[83],"retraining.":[84],"To":[85],"overcome":[86],"these":[87],"efficiency":[88],"extensibility":[90],"bottlenecks,":[91],"we":[92],"propose":[93],"\\textbf{DiTTo},":[94],"novel":[96],"order-aware":[97],"framework":[101],"consisting":[102],"DiTTo":[105,109,112,136,191],"Simulator":[106,113],"Agent.":[110],"The":[111],"combines":[114],"$\\cup$S-IR":[115],"for":[116,122],"single-step":[117],"restoration-action":[118],"simulation":[119],"AiO-IQA":[121],"per-action":[123],"quality":[124,197],"prediction,":[125],"reducing":[126],"ORTD":[127],"construction":[128],"$\\mathcal{O}(N^{\\mathbf{D}})$":[130],"simulator":[131],"image;":[134],"Agent":[137,192],"is":[138],"trained":[139],"by":[140,147],"SFT":[141],"on":[142],"simulator-generated":[144],"ORTD,":[145],"followed":[146],"\\textbf{Order-aware":[148],"Restoration":[149],"Alignment":[150],"(ORA)}":[151],"that":[152],"aligns":[153],"identification,":[155],"restoration-action-ordering,":[156],"output":[158],"format":[159],"along":[160],"independent":[161],"axes.":[162],"This":[163],"enables":[164],"\\textbf{plug-and-play":[165],"scalable":[166],"extensibility}:":[167],"adding":[168],"new":[170],"requires":[172],"updating":[173],"only":[174],"lightweight":[176],"ORA":[177],"stage.":[178],"On":[179],"MiO-100":[181],"evaluation":[182],"set":[183],"with":[184],"up":[185],"five":[187],"concurrent":[188],"degradations,":[189],"our":[190],"achieves":[193],"state-of-the-art":[194],"multi-degradation":[195],"among":[198],"previous":[199],"IR":[201],"methods.":[202]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-06-02T00:00:00"}
