{"id":"https://openalex.org/W2981847167","doi":"https://doi.org/10.1145/3343031.3351069","title":"Zero-Shot Restoration of Back-lit Images Using Deep Internal Learning","display_name":"Zero-Shot Restoration of Back-lit Images Using Deep Internal Learning","publication_year":2019,"publication_date":"2019-10-15","ids":{"openalex":"https://openalex.org/W2981847167","doi":"https://doi.org/10.1145/3343031.3351069","mag":"2981847167"},"language":"en","primary_location":{"id":"doi:10.1145/3343031.3351069","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3343031.3351069","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100351849","display_name":"Lin Zhang","orcid":"https://orcid.org/0000-0002-4360-5523"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Zhang","raw_affiliation_strings":["Tongji University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100448160","display_name":"Lijun Zhang","orcid":"https://orcid.org/0000-0002-6944-1918"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lijun Zhang","raw_affiliation_strings":["Tongji University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100441084","display_name":"Xiao Liu","orcid":"https://orcid.org/0000-0002-7888-6898"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Liu","raw_affiliation_strings":["Tongji University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021739501","display_name":"Ying Shen","orcid":"https://orcid.org/0000-0002-2966-7955"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Shen","raw_affiliation_strings":["Tongji University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040425424","display_name":"Shaoming Zhang","orcid":"https://orcid.org/0000-0001-8040-3894"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaoming Zhang","raw_affiliation_strings":["Tongji University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035948567","display_name":"Shengjie Zhao","orcid":"https://orcid.org/0000-0002-6109-2522"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengjie Zhao","raw_affiliation_strings":["Tongji University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":166,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1623","last_page":"1631"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9995999932289124,"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":0.9994000196456909,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.800900399684906},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.787300705909729},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.7421259880065918},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6194937229156494},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5866091251373291},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5538274645805359},{"id":"https://openalex.org/keywords/standard-test-image","display_name":"Standard test image","score":0.5441568493843079},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.49506106972694397},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4940188527107239},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.48356935381889343},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.45889851450920105},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.43101435899734497},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4264020621776581},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.4155576527118683},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3995862603187561},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.28425246477127075},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.23177212476730347},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13223227858543396}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.800900399684906},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.787300705909729},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.7421259880065918},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6194937229156494},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5866091251373291},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5538274645805359},{"id":"https://openalex.org/C180462255","wikidata":"https://www.wikidata.org/wiki/Q3559736","display_name":"Standard test image","level":4,"score":0.5441568493843079},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.49506106972694397},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4940188527107239},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.48356935381889343},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.45889851450920105},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.43101435899734497},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4264020621776581},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.4155576527118683},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3995862603187561},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.28425246477127075},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.23177212476730347},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13223227858543396},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3343031.3351069","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3343031.3351069","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.7799999713897705}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1534503689","https://openalex.org/W1669383326","https://openalex.org/W1972612668","https://openalex.org/W1978989063","https://openalex.org/W2017740444","https://openalex.org/W2028219289","https://openalex.org/W2042851294","https://openalex.org/W2068403421","https://openalex.org/W2069281566","https://openalex.org/W2116645175","https://openalex.org/W2125188192","https://openalex.org/W2128254161","https://openalex.org/W2141957843","https://openalex.org/W2150721269","https://openalex.org/W2160396317","https://openalex.org/W2165107586","https://openalex.org/W2293879958","https://openalex.org/W2767269772","https://openalex.org/W2799265886","https://openalex.org/W2897394382","https://openalex.org/W2963629411","https://openalex.org/W2963704386","https://openalex.org/W2963739249","https://openalex.org/W3172624883","https://openalex.org/W3177525997","https://openalex.org/W4402776467"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W4312814274","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W2116498084"],"abstract_inverted_index":{"How":[0],"to":[1,26,78,106,117],"restore":[2],"back-lit":[3,39,87,132,159],"images":[4,133],"still":[5],"remains":[6],"a":[7,35,64,143],"challenging":[8],"task.":[9],"State-of-the-art":[10],"methods":[11],"in":[12],"this":[13,31],"field":[14],"are":[15,23],"based":[16],"on":[17,53,129],"supervised":[18],"learning":[19],"and":[20,121],"thus":[21],"they":[22],"usually":[24],"restricted":[25],"specific":[27],"training":[28],"data.":[29],"In":[30],"paper,":[32],"we":[33,62],"propose":[34],"\"zero-shot\"":[36],"scheme":[37,153],"for":[38,71],"image":[40,56,96,160],"restoration,":[41],"which":[42],"exploits":[43],"the":[44,80,85,90,94,140,147,155,165,168],"power":[45],"of":[46,123,149],"deep":[47],"learning,":[48],"but":[49],"does":[50],"not":[51],"rely":[52],"any":[54],"prior":[55,59],"examples":[57],"or":[58],"training.":[60],"Specifically,":[61],"train":[63],"small":[65],"image-specific":[66],"CNN,":[67],"namely":[68],"ExCNet":[69,102],"(short":[70],"Exposure":[72],"Correction":[73],"Network)":[74],"at":[75,173],"test":[76,86,95],"time,":[77],"estimate":[79],"\"S-curve\"":[81],"that":[82,135],"best":[83,148],"fits":[84],"image.":[88,110],"Once":[89],"S-curve":[91],"is":[92,154,171],"estimated,":[93],"can":[97,103,138],"be":[98],"then":[99],"restored":[100],"straightforwardly.":[101],"adapt":[104],"itself":[105],"different":[107,118],"settings":[108],"per":[109],"This":[111],"makes":[112],"our":[113,136,150,152],"approach":[114,137],"widely":[115],"applicable":[116],"shooting":[119],"scenes":[120],"kinds":[122],"back-lighting":[124],"conditions.":[125],"Statistical":[126],"studies":[127],"performed":[128],"1512":[130],"real":[131],"demonstrate":[134],"outperform":[139],"competitors":[141],"by":[142],"large":[144],"margin.":[145],"To":[146,163],"knowledge,":[151],"first":[156],"unsupervised":[157],"CNN-based":[158],"restoration":[161],"method.":[162],"make":[164],"results":[166],"reproducible,":[167],"source":[169],"code":[170],"available":[172],"https://cslinzhang.github.io/ExCNet/.":[174]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":34},{"year":2024,"cited_by_count":44},{"year":2023,"cited_by_count":41},{"year":2022,"cited_by_count":28},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}