{"id":"https://openalex.org/W7124424972","doi":"https://doi.org/10.48550/arxiv.2601.09823","title":"NanoSD: Edge Efficient Foundation Model for Real Time Image Restoration","display_name":"NanoSD: Edge Efficient Foundation Model for Real Time Image Restoration","publication_year":2026,"publication_date":"2026-01-14","ids":{"openalex":"https://openalex.org/W7124424972","doi":"https://doi.org/10.48550/arxiv.2601.09823"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2601.09823","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.09823","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2601.09823","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088351438","display_name":"Subhajit Sanyal","orcid":"https://orcid.org/0009-0008-8787-6297"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Sanyal, Subhajit","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057645083","display_name":"Srinivas Soumitri Miriyala","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Miriyala, Srinivas Soumitri","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123248261","display_name":"Akshay Janardan Bankar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bankar, Akshay Janardan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Arveti, Manjunath","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Arveti, Manjunath","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123173907","display_name":"Harshit","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vajrala, Sowmya","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Pandith, Shreyas","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pandith, Shreyas","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Kodavanti, Sravanth","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kodavanti, Sravanth","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Ameta, Abhishek","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ameta, Abhishek","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123315794","display_name":"Harshit","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Harshit","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5017744333","display_name":"Amit Satish Unde","orcid":"https://orcid.org/0000-0002-3874-1272"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Unde, Amit Satish","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":10,"corresponding_author_ids":["https://openalex.org/A5088351438"],"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.6549999713897705,"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":0.6549999713897705,"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":0.26089999079704285,"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/T11448","display_name":"Face recognition and analysis","score":0.013700000010430813,"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":0.5651999711990356},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5184000134468079},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4959000051021576},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.48190000653266907},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.46779999136924744},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4593999981880188},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.43689998984336853},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.4320000112056732},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4172999858856201},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4068000018596649}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6392999887466431},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5978000164031982},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.5651999711990356},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5184000134468079},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5073999762535095},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4959000051021576},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.48190000653266907},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.46779999136924744},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4593999981880188},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.43689998984336853},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.4320000112056732},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4172999858856201},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4068000018596649},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.40380001068115234},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.40230000019073486},{"id":"https://openalex.org/C184408114","wikidata":"https://www.wikidata.org/wiki/Q1502022","display_name":"Generative Design","level":3,"score":0.39149999618530273},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.38940000534057617},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.38179999589920044},{"id":"https://openalex.org/C55128770","wikidata":"https://www.wikidata.org/wiki/Q5275440","display_name":"Diffusion map","level":4,"score":0.3693999946117401},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3366999924182892},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.3240000009536743},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.3160000145435333},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30239999294281006},{"id":"https://openalex.org/C4069607","wikidata":"https://www.wikidata.org/wiki/Q868732","display_name":"Aliasing","level":3,"score":0.296999990940094},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.295199990272522},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.29249998927116394},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.28600001335144043},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.28439998626708984},{"id":"https://openalex.org/C2781089630","wikidata":"https://www.wikidata.org/wiki/Q21856745","display_name":"Realization (probability)","level":2,"score":0.28200000524520874},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.2802000045776367},{"id":"https://openalex.org/C203504353","wikidata":"https://www.wikidata.org/wiki/Q4765461","display_name":"Anisotropic diffusion","level":3,"score":0.2685999870300293},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2596000134944916},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.25429999828338623},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.25290000438690186}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2601.09823","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.09823","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2601.09823","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.09823","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"score":0.5497315526008606,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Latent":[0],"diffusion":[1,43,65,178,191],"models":[2,67,101,179],"such":[3],"as":[4,156],"Stable":[5,70],"Diffusion":[6,71],"1.5":[7,72],"offer":[8],"strong":[9],"generative":[10,77,97],"priors":[11],"that":[12,102,125],"are":[13],"highly":[14],"valuable":[15],"for":[16,27,196],"image":[17,165,167],"restoration,":[18,170],"yet":[19],"their":[20],"full":[21],"pipelines":[22],"remain":[23],"too":[24],"computationally":[25],"heavy":[26],"deployment":[28],"on":[29,120,202],"edge":[30,203],"devices.":[31,204],"Existing":[32],"lightweight":[33,177],"variants":[34],"predominantly":[35],"compress":[36],"the":[37,42,47,86,89,96,108],"denoising":[38],"U-Net":[39,87],"or":[40],"reduce":[41],"trajectory,":[44],"which":[45],"disrupts":[46],"underlying":[48],"latent":[49],"manifold":[50],"and":[51,79,88,135,146,171,184,200],"limits":[52],"generalization":[53],"beyond":[54],"a":[55,61,157,189],"single":[56],"task.":[57],"We":[58,123],"introduce":[59],"NanoSD,":[60],"family":[62,194],"of":[63],"Pareto-optimal":[64],"foundation":[66,192],"distilled":[68],"from":[69],"through":[73],"network":[74],"surgery,":[75],"feature-wise":[76],"distillation,":[78],"structured":[80],"architectural":[81,142],"scaling":[82],"jointly":[83,149],"applied":[84],"to":[85,118],"VAE":[90],"encoder-decoder.":[91],"This":[92],"full-pipeline":[93],"co-design":[94],"preserves":[95],"prior":[98,176],"while":[99],"producing":[100],"occupy":[103],"distinct":[104],"operating":[105],"points":[106],"along":[107],"accuracy-latency-size":[109],"frontier":[110],"(e.g.,":[111],"130M-315M":[112],"parameters,":[113],"achieving":[114],"real-time":[115,197],"inference":[116],"down":[117],"20ms":[119],"mobile-class":[121],"NPUs).":[122],"show":[124],"parameter":[126],"reduction":[127],"alone":[128],"does":[129],"not":[130],"correlate":[131],"with":[132],"hardware":[133],"efficiency,":[134],"we":[136],"provide":[137],"an":[138],"analysis":[139],"revealing":[140],"how":[141],"balance,":[143],"feature":[144],"routing,":[145],"latent-space":[147],"preservation":[148],"shape":[150],"true":[151],"on-device":[152],"latency.":[153],"When":[154],"used":[155],"drop-in":[158],"backbone,":[159],"NanoSD":[160,187],"enables":[161],"state-of-the-art":[162],"performance":[163],"across":[164],"super-resolution,":[166],"deblurring,":[168],"face":[169],"monocular":[172],"depth":[173],"estimation,":[174],"outperforming":[175],"in":[180],"both":[181],"perceptual":[182],"quality":[183],"practical":[185],"deployability.":[186],"establishes":[188],"general-purpose":[190],"model":[193],"suitable":[195],"visual":[198],"generation":[199],"restoration":[201]},"counts_by_year":[],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2026-01-17T00:00:00"}