{"id":"https://openalex.org/W7161805734","doi":"https://doi.org/10.48550/arxiv.2605.19982","title":"InterLight: Leveraging Intrinsic Illumination Priors for Low-Light Image Enhancement","display_name":"InterLight: Leveraging Intrinsic Illumination Priors for Low-Light Image Enhancement","publication_year":2026,"publication_date":"2026-05-19","ids":{"openalex":"https://openalex.org/W7161805734","doi":"https://doi.org/10.48550/arxiv.2605.19982"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.19982","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.19982","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.2605.19982","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136573723","display_name":"Ziqi Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Ziqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136596356","display_name":"Xu Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072913037","display_name":"Laibin Chang","orcid":"https://orcid.org/0000-0002-6510-4359"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chang, Laibin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136558092","display_name":"Shi Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Shi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136590031","display_name":"Jiaqi W. Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Jiaqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136608396","display_name":"Huan Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Huan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"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":0.9908000230789185,"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":0.9908000230789185,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.0026000000070780516,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.0024999999441206455,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/color-constancy","display_name":"Color constancy","score":0.7918000221252441},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.7749999761581421},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.49709999561309814},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.48989999294281006},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4812000095844269},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.47999998927116394},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.46720001101493835},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.45509999990463257},{"id":"https://openalex.org/keywords/global-illumination","display_name":"Global illumination","score":0.41999998688697815}],"concepts":[{"id":"https://openalex.org/C187888035","wikidata":"https://www.wikidata.org/wiki/Q2563885","display_name":"Color constancy","level":3,"score":0.7918000221252441},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.7749999761581421},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6858999729156494},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6261000037193298},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.546500027179718},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.49709999561309814},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.48989999294281006},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4812000095844269},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.47999998927116394},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.46720001101493835},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.45509999990463257},{"id":"https://openalex.org/C89720835","wikidata":"https://www.wikidata.org/wiki/Q1531701","display_name":"Global illumination","level":3,"score":0.41999998688697815},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.40880000591278076},{"id":"https://openalex.org/C129112856","wikidata":"https://www.wikidata.org/wiki/Q375479","display_name":"Standard illuminant","level":2,"score":0.4011000096797943},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.3898000121116638},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3828999996185303},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.3587999939918518},{"id":"https://openalex.org/C2776639384","wikidata":"https://www.wikidata.org/wiki/Q840396","display_name":"Ideal (ethics)","level":2,"score":0.35370001196861267},{"id":"https://openalex.org/C3020402766","wikidata":"https://www.wikidata.org/wiki/Q104376712","display_name":"Prior information","level":2,"score":0.34850001335144043},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.31779998540878296},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3003999888896942},{"id":"https://openalex.org/C2776196576","wikidata":"https://www.wikidata.org/wiki/Q196113","display_name":"Camouflage","level":2,"score":0.2824000120162964},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.27730000019073486},{"id":"https://openalex.org/C3017601658","wikidata":"https://www.wikidata.org/wiki/Q545981","display_name":"Image enhancement","level":3,"score":0.26269999146461487},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.26030001044273376},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.2590000033378601},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.2578999996185303},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2549999952316284}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.19982","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.19982","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.2605.19982","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.19982","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Low-Light":[0],"Image":[1],"Enhancement":[2],"(LLIE)":[3],"has":[4],"long":[5],"been":[6],"a":[7,64,121,150],"challenging":[8],"problem":[9],"in":[10,134,140],"low-level":[11],"vision,":[12],"as":[13],"insufficient":[14],"illumination":[15,36,73,114,162],"often":[16,50],"leads":[17],"to":[18,126],"low":[19],"contrast,":[20],"detail":[21],"loss,":[22,131],"and":[23,37,49,70,169],"noise.":[24],"Recent":[25],"studies":[26],"show":[27],"that":[28,67,80,154],"deep":[29],"learning-based":[30],"Retinex":[31],"theory":[32],"can":[33],"effectively":[34],"decouple":[35],"reflectance.":[38],"However,":[39],"existing":[40],"methods":[41],"frequently":[42],"suffer":[43],"from":[44],"over-enhancement":[45],"or":[46,54],"color":[47],"distortion,":[48],"assume":[51],"uniform":[52],"noise":[53],"ideal":[55],"lighting.":[56],"To":[57],"address":[58],"these":[59],"limitations,":[60],"we":[61],"propose":[62],"InterLight,":[63],"novel":[65],"framework":[66],"systematically":[68],"excavates":[69],"operationalizes":[71],"intrinsic":[72,123,161],"priors":[74,98],"for":[75,129],"LLIE.Our":[76],"core":[77],"insight":[78],"is":[79,147,187],"robust":[81],"enhancement":[82,173],"requires":[83],"not":[84],"just":[85],"estimating":[86],"illumination,":[87],"but":[88],"constructing":[89],"an":[90],"illumination-aware":[91],"pipeline.":[92],"We":[93],"first":[94],"inject":[95],"sensor-level":[96],"illumination-response":[97],"via":[99],"physics-guided":[100],"augmentation,":[101],"then":[102],"represent":[103],"the":[104,111,144,181],"degradation":[105],"through":[106],"adaptive":[107],"prompts":[108],"conditioned":[109],"on":[110],"scene's":[112],"latent":[113],"state.":[115],"This":[116],"explicit":[117],"representation":[118],"directly":[119],"guides":[120],"luminance-gated":[122],"memory":[124],"mechanism":[125],"selectively":[127],"compensate":[128],"information":[130],"prioritizing":[132],"reconstruction":[133],"dark":[135],"regions":[136],"while":[137],"preserving":[138],"fidelity":[139],"bright":[141],"ones.":[142],"Finally,":[143],"entire":[145],"process":[146],"regularized":[148],"by":[149],"self-supervised":[151],"consistency":[152],"objective":[153],"distills":[155],"illumination-invariant":[156],"features.":[157],"By":[158],"deeply":[159],"exploiting":[160],"priors,":[163],"our":[164,184],"method":[165],"achieves":[166],"clearer":[167],"textures":[168],"more":[170],"visually":[171],"coherent":[172],"results.":[174],"Extensive":[175],"experiments":[176],"across":[177],"multiple":[178],"benchmarks":[179],"demonstrate":[180],"effectiveness":[182],"of":[183],"approach.":[185],"Code":[186],"available":[188],"at:":[189],"https://github.com/House-yuyu/InterLight.":[190]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-21T00:00:00"}