{"id":"https://openalex.org/W4390872154","doi":"https://doi.org/10.1109/iccv51070.2023.01207","title":"Low-Light Image Enhancement with Illumination-Aware Gamma Correction and Complete Image Modelling Network","display_name":"Low-Light Image Enhancement with Illumination-Aware Gamma Correction and Complete Image Modelling Network","publication_year":2023,"publication_date":"2023-10-01","ids":{"openalex":"https://openalex.org/W4390872154","doi":"https://doi.org/10.1109/iccv51070.2023.01207"},"language":"en","primary_location":{"id":"doi:10.1109/iccv51070.2023.01207","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51070.2023.01207","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CVF International Conference on Computer Vision (ICCV)","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/A5100703786","display_name":"Yinglong Wang","orcid":"https://orcid.org/0000-0001-7080-5144"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yinglong Wang","raw_affiliation_strings":["Meituan Inc"],"affiliations":[{"raw_affiliation_string":"Meituan Inc","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100412040","display_name":"Zhen Liu","orcid":"https://orcid.org/0000-0002-2804-1133"},"institutions":[{"id":"https://openalex.org/I4210109870","display_name":"Vi Technology (United States)","ror":"https://ror.org/016mnbp44","country_code":"US","type":"company","lineage":["https://openalex.org/I4210109870"]},{"id":"https://openalex.org/I4401726805","display_name":"Megvii (China)","ror":"https://ror.org/040b32p69","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726805"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhen Liu","raw_affiliation_strings":["Megvii Technology"],"affiliations":[{"raw_affiliation_string":"Megvii Technology","institution_ids":["https://openalex.org/I4210109870","https://openalex.org/I4401726805"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039205892","display_name":"Jianzhuang Liu","orcid":"https://orcid.org/0000-0002-7960-9382"},"institutions":[{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianzhuang Liu","raw_affiliation_strings":["Shenzhen Institute of Advanced Technology"],"affiliations":[{"raw_affiliation_string":"Shenzhen Institute of Advanced Technology","institution_ids":["https://openalex.org/I4210145761"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030497493","display_name":"Songcen Xu","orcid":"https://orcid.org/0000-0002-0022-0906"},"institutions":[{"id":"https://openalex.org/I4210159102","display_name":"Huawei Technologies (Sweden)","ror":"https://ror.org/0500fyd17","country_code":"SE","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210159102"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Songcen Xu","raw_affiliation_strings":["Huawei Noah&#x2019;s Ark Lab"],"affiliations":[{"raw_affiliation_string":"Huawei Noah&#x2019;s Ark Lab","institution_ids":["https://openalex.org/I4210159102"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039387461","display_name":"Shuaicheng Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I4401726805","display_name":"Megvii (China)","ror":"https://ror.org/040b32p69","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726805"]},{"id":"https://openalex.org/I4210109870","display_name":"Vi Technology (United States)","ror":"https://ror.org/016mnbp44","country_code":"US","type":"company","lineage":["https://openalex.org/I4210109870"]},{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Shuaicheng Liu","raw_affiliation_strings":["University of Electronic Science and Technology of China","Megvii Technology"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"Megvii Technology","institution_ids":["https://openalex.org/I4210109870","https://openalex.org/I4401726805"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100703786"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.2707,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.96942305,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"13082","last_page":"13091"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9975000023841858,"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":0.9955000281333923,"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":0.7591124176979065},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7120055556297302},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6143741011619568},{"id":"https://openalex.org/keywords/gamma-correction","display_name":"Gamma correction","score":0.5421311855316162},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5347776412963867},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.530901312828064},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.500544548034668},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4589364230632782},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4363780915737152},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3774257302284241},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.132761150598526}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7591124176979065},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7120055556297302},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6143741011619568},{"id":"https://openalex.org/C17916492","wikidata":"https://www.wikidata.org/wiki/Q1144257","display_name":"Gamma correction","level":3,"score":0.5421311855316162},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5347776412963867},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.530901312828064},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.500544548034668},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4589364230632782},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4363780915737152},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3774257302284241},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.132761150598526},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccv51070.2023.01207","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51070.2023.01207","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CVF International Conference on Computer Vision (ICCV)","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":57,"referenced_works":["https://openalex.org/W1990675808","https://openalex.org/W2011592399","https://openalex.org/W2054814429","https://openalex.org/W2121900453","https://openalex.org/W2133665775","https://openalex.org/W2154549868","https://openalex.org/W2254039850","https://openalex.org/W2412926690","https://openalex.org/W2468596194","https://openalex.org/W2566376500","https://openalex.org/W2752782242","https://openalex.org/W2791710889","https://openalex.org/W2799265886","https://openalex.org/W2981718299","https://openalex.org/W3003838261","https://openalex.org/W3007628345","https://openalex.org/W3015044426","https://openalex.org/W3034527052","https://openalex.org/W3034539499","https://openalex.org/W3035229960","https://openalex.org/W3035731588","https://openalex.org/W3083040138","https://openalex.org/W3106758205","https://openalex.org/W3119525307","https://openalex.org/W3120540810","https://openalex.org/W3121661546","https://openalex.org/W3125869362","https://openalex.org/W3133696297","https://openalex.org/W3134765225","https://openalex.org/W3143419403","https://openalex.org/W3164024107","https://openalex.org/W3171125843","https://openalex.org/W3174792937","https://openalex.org/W3204478975","https://openalex.org/W3207918547","https://openalex.org/W3212044080","https://openalex.org/W3214264009","https://openalex.org/W4214665850","https://openalex.org/W4285160480","https://openalex.org/W4295312788","https://openalex.org/W4312249431","https://openalex.org/W4312536154","https://openalex.org/W4312560884","https://openalex.org/W4312579682","https://openalex.org/W4312654281","https://openalex.org/W4312725970","https://openalex.org/W4312812783","https://openalex.org/W4313059954","https://openalex.org/W4385245566","https://openalex.org/W4386076583","https://openalex.org/W6631190155","https://openalex.org/W6739901393","https://openalex.org/W6754146604","https://openalex.org/W6766978945","https://openalex.org/W6774322041","https://openalex.org/W6790690058","https://openalex.org/W6795475546"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2745001401","https://openalex.org/W4321353415","https://openalex.org/W2130974462","https://openalex.org/W972276598","https://openalex.org/W4246352526","https://openalex.org/W2028665553","https://openalex.org/W4230315250","https://openalex.org/W2086519370","https://openalex.org/W2087343574"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,72,135,150,171],"novel":[4,136],"network":[5],"structure":[6],"with":[7,54],"illumination-aware":[8],"gamma":[9,52,67,98],"correction":[10,53,65],"and":[11,103],"complete":[12],"image":[13,19],"modelling":[14,57,117],"to":[15,26,41,47,68,74,92,96,125,139],"solve":[16],"the":[17,49,55,64,80,101,142,164],"low-light":[18,37,113,131],"enhancement":[20],"problem.":[21],"Low-light":[22],"environments":[23],"usually":[24,108],"lead":[25],"less":[27],"informative":[28,168],"large-scale":[29],"dark":[30,157],"areas,":[31],"directly":[32],"learning":[33],"deep":[34,60],"representations":[35],"from":[36,166],"images":[38,148],"is":[39],"insensitive":[40],"recovering":[42],"normal":[43],"illumination.":[44,82],"We":[45,133],"propose":[46,91,134],"integrate":[48],"effectiveness":[50],"of":[51,59,144],"strong":[56],"capacities":[58],"networks,":[61],"which":[62],"enables":[63],"factor":[66],"be":[69,160],"learned":[70],"in":[71,112,170],"coarse":[73],"elaborate":[75],"manner":[76],"via":[77,149],"adaptively":[78],"perceiving":[79],"deviated":[81],"Because":[83],"exponential":[84],"operation":[85],"introduces":[86],"high":[87],"computational":[88],"complexity,":[89],"we":[90],"use":[93],"Taylor":[94],"Series":[95],"approximate":[97],"correction,":[99],"accelerating":[100],"training":[102],"inference":[104],"speed.":[105],"Dark":[106],"areas":[107,158],"occupy":[109],"large":[110],"scales":[111],"images,":[114],"common":[115],"local":[116],"structures,":[118],"e.g.,":[119],"CNN,":[120],"SwinIR,":[121],"are":[122],"thus":[123],"insufficient":[124],"recover":[126],"accurate":[127],"illumination":[128],"across":[129,147],"whole":[130],"images.":[132],"Transformer":[137],"block":[138],"completely":[140],"simulate":[141],"dependencies":[143],"all":[145],"pixels":[146],"local-to-global":[151],"hierarchical":[152],"attention":[153],"mechanism,":[154],"so":[155],"that":[156,182],"could":[159],"inferred":[161],"by":[162],"borrowing":[163],"information":[165],"far":[167],"regions":[169],"highly":[172],"effective":[173],"manner.":[174],"Extensive":[175],"experiments":[176],"on":[177],"several":[178],"benchmark":[179],"datasets":[180],"demonstrate":[181],"our":[183],"approach":[184],"outperforms":[185],"state-of-the-art":[186],"methods.":[187]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":25},{"year":2024,"cited_by_count":16}],"updated_date":"2026-02-27T16:54:17.756197","created_date":"2025-10-10T00:00:00"}
