{"id":"https://openalex.org/W4412170788","doi":"https://doi.org/10.1109/access.2025.3587789","title":"An Efficient Uncertainty-Driven Learning for Stochastic Super-Resolution","display_name":"An Efficient Uncertainty-Driven Learning for Stochastic Super-Resolution","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412170788","doi":"https://doi.org/10.1109/access.2025.3587789"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3587789","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3587789","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3587789","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044851404","display_name":"Daeyoung Han","orcid":"https://orcid.org/0000-0003-0368-8675"},"institutions":[{"id":"https://openalex.org/I39534123","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78","country_code":"KR","type":"education","lineage":["https://openalex.org/I39534123"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Daeyoung Han","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea","The School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-0368-8675","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea","institution_ids":["https://openalex.org/I39534123"]},{"raw_affiliation_string":"The School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea","institution_ids":["https://openalex.org/I39534123"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048161957","display_name":"Seongmin Hwang","orcid":"https://orcid.org/0000-0003-3313-8586"},"institutions":[{"id":"https://openalex.org/I39534123","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78","country_code":"KR","type":"education","lineage":["https://openalex.org/I39534123"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seongmin Hwang","raw_affiliation_strings":["AI Graduate School, Gwangju Institute of Science and Technology, Gwangju, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-3313-8586","affiliations":[{"raw_affiliation_string":"AI Graduate School, Gwangju Institute of Science and Technology, Gwangju, South Korea","institution_ids":["https://openalex.org/I39534123"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090069528","display_name":"Hyunseok Ahn","orcid":"https://orcid.org/0009-0007-1803-5059"},"institutions":[{"id":"https://openalex.org/I24541011","display_name":"Soonchunhyang University","ror":"https://ror.org/03qjsrb10","country_code":"KR","type":"education","lineage":["https://openalex.org/I24541011"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hoyeon Ahn","raw_affiliation_strings":["Department of Metaverse and Game, Soonchunhyang University, Asan, South Korea"],"raw_orcid":"https://orcid.org/0009-0007-1803-5059","affiliations":[{"raw_affiliation_string":"Department of Metaverse and Game, Soonchunhyang University, Asan, South Korea","institution_ids":["https://openalex.org/I24541011"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056743652","display_name":"Moongu Jeon","orcid":"https://orcid.org/0000-0002-2775-7789"},"institutions":[{"id":"https://openalex.org/I39534123","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78","country_code":"KR","type":"education","lineage":["https://openalex.org/I39534123"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Moongu Jeon","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea","The School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-2775-7789","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea","institution_ids":["https://openalex.org/I39534123"]},{"raw_affiliation_string":"The School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea","institution_ids":["https://openalex.org/I39534123"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12891761,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":null,"first_page":"123344","last_page":"123354"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9787999987602234,"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":0.9787999987602234,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9717000126838684,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9398999810218811,"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/computer-science","display_name":"Computer science","score":0.6864376068115234},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40130627155303955}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6864376068115234},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40130627155303955}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3587789","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3587789","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:2713d0ed11504671aa9985811cf73951","is_oa":true,"landing_page_url":"https://doaj.org/article/2713d0ed11504671aa9985811cf73951","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 123344-123354 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3587789","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3587789","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321301","display_name":"Soonchunhyang University","ror":"https://ror.org/03qjsrb10"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W1885185971","https://openalex.org/W1930824406","https://openalex.org/W2108598243","https://openalex.org/W2121927366","https://openalex.org/W2126926806","https://openalex.org/W2133665775","https://openalex.org/W2192954843","https://openalex.org/W2503339013","https://openalex.org/W2618530766","https://openalex.org/W2739757502","https://openalex.org/W2768814045","https://openalex.org/W2866634454","https://openalex.org/W2952773607","https://openalex.org/W2954930822","https://openalex.org/W2962770929","https://openalex.org/W2962785568","https://openalex.org/W2962974533","https://openalex.org/W2963372104","https://openalex.org/W2963470893","https://openalex.org/W2963814095","https://openalex.org/W2964101377","https://openalex.org/W3007447735","https://openalex.org/W3013529009","https://openalex.org/W3095495550","https://openalex.org/W3155072588","https://openalex.org/W3172534136","https://openalex.org/W3174589446","https://openalex.org/W3180355996","https://openalex.org/W3184054654","https://openalex.org/W3187338951","https://openalex.org/W3199532396","https://openalex.org/W3207918547","https://openalex.org/W4226014430","https://openalex.org/W4250482878","https://openalex.org/W4312933868","https://openalex.org/W4320013936","https://openalex.org/W4382462760","https://openalex.org/W4386065592","https://openalex.org/W4386076141","https://openalex.org/W4386076458","https://openalex.org/W4386083034","https://openalex.org/W4400582020","https://openalex.org/W6631190155","https://openalex.org/W6679045638","https://openalex.org/W6690026940","https://openalex.org/W6745560452","https://openalex.org/W6748582592","https://openalex.org/W6779823529","https://openalex.org/W6783713337","https://openalex.org/W6797359156","https://openalex.org/W6803132585","https://openalex.org/W6846186599","https://openalex.org/W6855261814","https://openalex.org/W6857566199","https://openalex.org/W6873847477","https://openalex.org/W7006356007"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Single":[0],"image":[1,18],"super-resolution":[2],"(SISR)":[3],"is":[4,96],"inherently":[5],"ill-posed":[6],"because":[7],"of":[8,92,118,148],"information":[9],"loss":[10],"during":[11],"degradation,":[12],"where":[13],"a":[14,56,100,106,133],"single":[15],"low-resolution":[16],"(LR)":[17],"corresponds":[19],"to":[20,88,102],"multiple":[21],"plausible":[22],"high-resolution":[23],"(HR)":[24],"reconstructions.":[25],"While":[26],"recent":[27],"stochastic":[28,61],"SISR":[29,62,108,120],"approaches":[30],"address":[31],"this":[32,52],"by":[33,69,128,160],"modeling":[34],"conditional":[35],"distributions,":[36],"they":[37],"commonly":[38],"assume":[39],"isotropic":[40],"Gaussian":[41,66],"priors,":[42],"overlooking":[43],"spatial":[44],"variations":[45],"in":[46,146,162,166],"uncertainty":[47,71,81],"across":[48],"the":[49,77,90,115,119,130,156],"image.":[50],"In":[51],"paper,":[53],"we":[54],"propose":[55],"novel":[57],"uncertainty-driven":[58],"framework":[59],"for":[60],"that":[63,140],"incorporates":[64],"anisotropic":[65],"priors":[67],"modulated":[68],"estimated":[70],"maps.":[72],"Our":[73],"model":[74],"explicitly":[75],"learns":[76],"spatially":[78],"varying":[79],"aleatoric":[80],"from":[82],"LR":[83],"inputs":[84],"and":[85,151,164],"uses":[86],"it":[87],"guide":[89],"sampling":[91],"latent":[93],"noise,":[94],"which":[95],"then":[97],"injected":[98],"into":[99],"decoder":[101],"reconstruct":[103],"residuals":[104],"over":[105],"deterministic":[107,135],"baseline.":[109],"This":[110],"approach":[111],"not":[112],"only":[113],"captures":[114],"one-to-many":[116],"nature":[117],"task":[121],"but":[122],"also":[123],"preserves":[124],"strong":[125],"pixel-level":[126],"fidelity":[127],"centering":[129],"generation":[131],"around":[132],"pre-trained":[134],"prediction.":[136],"Extensive":[137],"experiments":[138],"show":[139],"our":[141],"method":[142],"achieves":[143],"state-of-the-art":[144],"performance":[145],"terms":[147],"both":[149],"distortion":[150],"perceptual":[152],"quality,":[153],"especially":[154],"outperforming":[155],"best":[157],"generative-model-based":[158],"methods":[159],"+0.44":[161],"PSNR":[163],"-0.008":[165],"LPIPS":[167],"simultaneously":[168],"with":[169],"lower":[170],"computational":[171],"cost.":[172]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}