{"id":"https://openalex.org/W4416250957","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227798","title":"LightLLIE: Lightweight Low-Light Image Enhancement via Dual Attention and Re-parameterization","display_name":"LightLLIE: Lightweight Low-Light Image Enhancement via Dual Attention and Re-parameterization","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416250957","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227798"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11227798","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227798","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011675994","display_name":"Xi Wang","orcid":"https://orcid.org/0000-0002-1376-2712"},"institutions":[{"id":"https://openalex.org/I4210128818","display_name":"Institute of Software","ror":"https://ror.org/033dfsn42","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128818"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xi Wang","raw_affiliation_strings":["Institute of Software, Chinese Academy of Sciences,Beijing,China,100190"],"affiliations":[{"raw_affiliation_string":"Institute of Software, Chinese Academy of Sciences,Beijing,China,100190","institution_ids":["https://openalex.org/I4210128818","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100610889","display_name":"Quan Zheng","orcid":"https://orcid.org/0000-0001-5053-5511"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210128818","display_name":"Institute of Software","ror":"https://ror.org/033dfsn42","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128818"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quan Zheng","raw_affiliation_strings":["Institute of Software, Chinese Academy of Sciences,Beijing,China,100190"],"affiliations":[{"raw_affiliation_string":"Institute of Software, Chinese Academy of Sciences,Beijing,China,100190","institution_ids":["https://openalex.org/I4210128818","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5011675994"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210128818"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37374114,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9922000169754028,"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":0.9922000169754028,"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":0.001500000013038516,"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":0.00139999995008111,"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/brightness","display_name":"Brightness","score":0.7293999791145325},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5378000140190125},{"id":"https://openalex.org/keywords/image-enhancement","display_name":"Image enhancement","score":0.4117000102996826},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.39969998598098755},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.38190001249313354},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.36480000615119934},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.35339999198913574},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.3492000102996826}],"concepts":[{"id":"https://openalex.org/C125245961","wikidata":"https://www.wikidata.org/wiki/Q221656","display_name":"Brightness","level":2,"score":0.7293999791145325},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.70169997215271},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5378000140190125},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.519599974155426},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4700999855995178},{"id":"https://openalex.org/C3017601658","wikidata":"https://www.wikidata.org/wiki/Q545981","display_name":"Image enhancement","level":3,"score":0.4117000102996826},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.39969998598098755},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.38190001249313354},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.36480000615119934},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.35339999198913574},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.3492000102996826},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.3425999879837036},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3382999897003174},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3334999978542328},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.28600001335144043},{"id":"https://openalex.org/C8641274","wikidata":"https://www.wikidata.org/wiki/Q1030958","display_name":"Tone mapping","level":4,"score":0.2840000092983246},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.26820001006126404},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.26420000195503235},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2563000023365021},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.25189998745918274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11227798","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227798","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1580436348","https://openalex.org/W1987444808","https://openalex.org/W2054814429","https://openalex.org/W2076205488","https://openalex.org/W2102166818","https://openalex.org/W2116973876","https://openalex.org/W2128926607","https://openalex.org/W2133665775","https://openalex.org/W2150461190","https://openalex.org/W2566376500","https://openalex.org/W2791710889","https://openalex.org/W2962785568","https://openalex.org/W2963766909","https://openalex.org/W2981609437","https://openalex.org/W3013338555","https://openalex.org/W3034895805","https://openalex.org/W3035731588","https://openalex.org/W3120540810","https://openalex.org/W3125869362","https://openalex.org/W3134649899","https://openalex.org/W3167976421","https://openalex.org/W3171038842","https://openalex.org/W3174792937","https://openalex.org/W3214264009","https://openalex.org/W4289752563","https://openalex.org/W4310138363","https://openalex.org/W4312249431","https://openalex.org/W4313059954","https://openalex.org/W4319300236","https://openalex.org/W4375869153","https://openalex.org/W4377079834","https://openalex.org/W4385488592","https://openalex.org/W4385805076","https://openalex.org/W4386076204","https://openalex.org/W4387967967","https://openalex.org/W4389347891","https://openalex.org/W4389887658","https://openalex.org/W4402754006"],"related_works":[],"abstract_inverted_index":{"In":[0,59],"recent":[1],"years,":[2],"significant":[3],"advancements":[4],"have":[5,25],"been":[6],"made":[7],"in":[8],"the":[9,17,31,128,134,137],"field":[10],"of":[11,19,33,136],"low-light":[12,71],"image":[13,72],"enhancement,":[14],"especially":[15],"with":[16,111],"emergence":[18],"transformer-":[20],"and":[21,50,101,119,153],"diffusion-based":[22],"models,":[23],"which":[24],"demonstrated":[26],"remarkable":[27],"enhancement":[28,73,94,105],"capabilities.":[29],"However,":[30],"introduction":[32],"these":[34],"advanced":[35],"but":[36],"sophisticated":[37],"neural":[38],"network":[39,77],"architectures":[40],"often":[41],"leads":[42],"to":[43,62,89],"algorithms":[44],"that":[45,157],"demand":[46],"extensive":[47],"computational":[48],"resources":[49],"storage":[51],"space,":[52],"hindering":[53],"their":[54],"applicability":[55],"on":[56],"resource-constrained":[57],"devices.":[58],"this":[60,64],"paper,":[61],"address":[63],"challenge,":[65],"we":[66],"propose":[67],"LightLLIE,":[68],"a":[69,79,83,91,102,108,142],"lightweight":[70,109],"network.":[74],"The":[75],"proposed":[76],"employs":[78],"global-local":[80],"dual-branch":[81],"architecture:":[82],"global":[84,92,129],"brightness":[85,93,98,130],"adjustment":[86,131],"branch":[87,106],"designed":[88],"formulate":[90],"scheme":[95],"by":[96],"analyzing":[97],"channel":[99],"information,":[100],"local":[103,117],"detail":[104,118],"employing":[107],"design":[110],"dual":[112],"attention":[113],"blocks":[114],"for":[115],"effective":[116],"texture":[120],"restoration.":[121],"Notably,":[122],"structural":[123],"re-parameterization":[124],"is":[125],"integrated":[126],"into":[127,141],"branch,":[132],"enabling":[133],"conversion":[135],"reparameterizable":[138],"multi-scale":[139],"convolution":[140],"simple":[143],"structure":[144],"during":[145],"inference,":[146],"thereby":[147],"improving":[148],"inference":[149],"efficiency.":[150],"Extensive":[151],"quantitative":[152],"qualitative":[154],"experiments":[155],"demonstrate":[156],"LightLLIE":[158],"outperforms":[159],"state-of-the-art":[160],"methods":[161],"while":[162],"achieving":[163],"superior":[164],"processing":[165],"speeds.":[166]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-14T00:00:00"}