{"id":"https://openalex.org/W4414384521","doi":"https://doi.org/10.1109/wacv61042.2026.00224","title":"Illuminating Darkness: Learning to Enhance Low-light Images In-the-Wild","display_name":"Illuminating Darkness: Learning to Enhance Low-light Images In-the-Wild","publication_year":2026,"publication_date":"2026-03-06","ids":{"openalex":"https://openalex.org/W4414384521","doi":"https://doi.org/10.1109/wacv61042.2026.00224"},"language":"en","primary_location":{"id":"doi:10.1109/wacv61042.2026.00224","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00224","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2503.06898","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009462221","display_name":"S M A Sharif","orcid":null},"institutions":[{"id":"https://openalex.org/I4210127161","display_name":"Observatorio de Prospectiva Tecnol\u00f3gica Industrial","ror":"https://ror.org/03f6cng42","country_code":"ES","type":"other","lineage":["https://openalex.org/I4210127161"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"S. M. A. Sharif","raw_affiliation_strings":["Opt-AI Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Opt-AI Inc","institution_ids":["https://openalex.org/I4210127161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100609764","display_name":"Abdur Rehman","orcid":"https://orcid.org/0000-0003-1510-0939"},"institutions":[{"id":"https://openalex.org/I4210127161","display_name":"Observatorio de Prospectiva Tecnol\u00f3gica Industrial","ror":"https://ror.org/03f6cng42","country_code":"ES","type":"other","lineage":["https://openalex.org/I4210127161"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Abdur Rehman","raw_affiliation_strings":["Opt-AI Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Opt-AI Inc","institution_ids":["https://openalex.org/I4210127161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057508230","display_name":"Zain Ul Abidin","orcid":"https://orcid.org/0009-0008-4706-6740"},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Zain Ul Abidin","raw_affiliation_strings":["Sejong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sejong University","institution_ids":["https://openalex.org/I28777354"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061687830","display_name":"Fayaz Ali Dharejo","orcid":"https://orcid.org/0000-0001-7685-3913"},"institutions":[{"id":"https://openalex.org/I25974101","display_name":"University of W\u00fcrzburg","ror":"https://ror.org/00fbnyb24","country_code":"DE","type":"education","lineage":["https://openalex.org/I25974101"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Fayaz Ali Dharejo","raw_affiliation_strings":["University of W&#x00FC;rzburg"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of W&#x00FC;rzburg","institution_ids":["https://openalex.org/I25974101"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052236177","display_name":"Radu Timofte","orcid":"https://orcid.org/0000-0002-1478-0402"},"institutions":[{"id":"https://openalex.org/I25974101","display_name":"University of W\u00fcrzburg","ror":"https://ror.org/00fbnyb24","country_code":"DE","type":"education","lineage":["https://openalex.org/I25974101"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Radu Timofte","raw_affiliation_strings":["University of W&#x00FC;rzburg"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of W&#x00FC;rzburg","institution_ids":["https://openalex.org/I25974101"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086213066","display_name":"Rizwan Ali Naqvi","orcid":"https://orcid.org/0000-0002-7473-8441"},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Rizwan Ali Naqvi","raw_affiliation_strings":["Sejong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sejong University","institution_ids":["https://openalex.org/I28777354"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00629333,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2263","last_page":"2272"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.3158000111579895,"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":0.3158000111579895,"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/chrominance","display_name":"Chrominance","score":0.7249000072479248},{"id":"https://openalex.org/keywords/luminance","display_name":"Luminance","score":0.5248000025749207},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.477400004863739},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.46720001101493835},{"id":"https://openalex.org/keywords/high-dynamic-range","display_name":"High dynamic range","score":0.45820000767707825},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4546999931335449},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4431999921798706},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.43790000677108765},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.426800012588501},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.41339999437332153}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7688000202178955},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7615000009536743},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7329999804496765},{"id":"https://openalex.org/C163204269","wikidata":"https://www.wikidata.org/wiki/Q355263","display_name":"Chrominance","level":3,"score":0.7249000072479248},{"id":"https://openalex.org/C73313986","wikidata":"https://www.wikidata.org/wiki/Q355386","display_name":"Luminance","level":2,"score":0.5248000025749207},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.477400004863739},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.46720001101493835},{"id":"https://openalex.org/C2780056265","wikidata":"https://www.wikidata.org/wiki/Q106239881","display_name":"High dynamic range","level":3,"score":0.45820000767707825},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4546999931335449},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4431999921798706},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.43790000677108765},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.426800012588501},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.41339999437332153},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.40869998931884766},{"id":"https://openalex.org/C32653426","wikidata":"https://www.wikidata.org/wiki/Q3813641","display_name":"Background subtraction","level":3,"score":0.38449999690055847},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.3506999909877777},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3167000114917755},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30720001459121704},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.30309998989105225},{"id":"https://openalex.org/C3019635856","wikidata":"https://www.wikidata.org/wiki/Q1619726","display_name":"Background image","level":3,"score":0.2969000041484833},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.29120001196861267},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.2906999886035919},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.2906999886035919},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.29030001163482666},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.2874000072479248},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.2842000126838684},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2637999951839447},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.26019999384880066},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2572999894618988},{"id":"https://openalex.org/C125245961","wikidata":"https://www.wikidata.org/wiki/Q221656","display_name":"Brightness","level":2,"score":0.2524000108242035}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/wacv61042.2026.00224","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00224","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2503.06898","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2503.06898","pdf_url":"https://arxiv.org/pdf/2503.06898","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":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2503.06898","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2503.06898","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:2503.06898","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2503.06898","pdf_url":"https://arxiv.org/pdf/2503.06898","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":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Single-shot":[0],"low-light":[1,82,154],"image":[2,55],"enhancement":[3],"(SLLIE)":[4],"remains":[5],"challenging":[6,42],"due":[7],"to":[8,105,129],"the":[9,23,35],"limited":[10],"availability":[11],"of":[12,41,119],"diverse,":[13],"realworld":[14],"paired":[15],"datasets.":[16],"To":[17,72,88],"bridge":[18],"this":[19],"gap,":[20],"we":[21,78,92],"introduce":[22],"Low-Light":[24],"Smartphone":[25],"Dataset":[26],"(LSD),":[27],"a":[28,38,95,112],"large-scale,":[29],"high-resolution":[30],"(4K+)":[31],"dataset":[32],"collected":[33],"in":[34],"wild":[36],"across":[37],"wide":[39],"range":[40],"lighting":[43],"conditions":[44],"(0.1\u2013200":[45],"lux).":[46],"LSD":[47,142],"contains":[48],"6,425":[49],"precisely":[50],"aligned":[51],"low":[52],"and":[53,63,69,75,101,126,134,146],"normallight":[54],"pairs,":[56],"selected":[57],"from":[58,84],"over":[59],"8,000":[60],"dynamic":[61],"indoor":[62],"outdoor":[64],"scenes":[65],"through":[66],"multi-frame":[67],"acquisition":[68],"expert":[70],"evaluation.":[71],"evaluate":[73],"generalization":[74],"aesthetic":[76],"quality,":[77],"collect":[79],"2,117":[80],"unpaired":[81],"images":[83],"previously":[85],"unseen":[86],"devices.":[87],"fully":[89],"exploit":[90],"LSD,":[91],"propose":[93,111],"TFFormer,":[94],"hybrid":[96],"model":[97],"that":[98],"encodes":[99],"luminance":[100],"chrominance":[102],"(LC)":[103],"separately":[104],"reduce":[106],"color-structure":[107],"entanglement.":[108],"We":[109],"further":[110],"cross-attention-driven":[113],"joint":[114],"decoder":[115],"for":[116],"context-aware":[117],"fusion":[118],"LC":[120,124],"representations,":[121],"along":[122],"with":[123],"refinement":[125],"LC-guided":[127],"supervision":[128],"significantly":[130],"enhance":[131],"perceptual":[132],"fidelity":[133],"structural":[135],"consistency.":[136],"TFFormer":[137],"achieves":[138],"state-of-the-art":[139],"results":[140],"on":[141,159],"(+2.45":[143],"dB":[144],"PSNR)":[145],"substantially":[147],"improves":[148],"downstream":[149],"vision":[150],"tasks,":[151],"such":[152],"as":[153],"object":[155],"detection":[156],"(+6.80":[157],"mAP":[158],"ExDark).":[160]},"counts_by_year":[],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2025-10-10T00:00:00"}
