{"id":"https://openalex.org/W3089687342","doi":"https://doi.org/10.1109/icip40778.2020.9191007","title":"Feature Aggregation Attention Network for Single Image Dehazing","display_name":"Feature Aggregation Attention Network for Single Image Dehazing","publication_year":2020,"publication_date":"2020-09-30","ids":{"openalex":"https://openalex.org/W3089687342","doi":"https://doi.org/10.1109/icip40778.2020.9191007","mag":"3089687342"},"language":"en","primary_location":{"id":"doi:10.1109/icip40778.2020.9191007","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9191007","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Image Processing (ICIP)","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/A5100306850","display_name":"Lan Yan","orcid":"https://orcid.org/0000-0001-6452-9649"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lan Yan","raw_affiliation_strings":["The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088111638","display_name":"Wenbo Zheng","orcid":"https://orcid.org/0000-0001-9732-3217"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenbo Zheng","raw_affiliation_strings":["School of Software Engineering, Xi\u2019an Jiaotong University, Xi\u2019an, China","School of Software Engineering, Xi'an Jiaotong University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Xi\u2019an Jiaotong University, Xi\u2019an, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"School of Software Engineering, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042895349","display_name":"Chao Gou","orcid":"https://orcid.org/0000-0002-4128-886X"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Gou","raw_affiliation_strings":["School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113600509","display_name":"Fei\u2013Yue Wang","orcid":"https://orcid.org/0000-0001-9185-3989"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei-Yue Wang","raw_affiliation_strings":["The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"923","last_page":"927"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":1.0,"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":1.0,"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":0.9976000189781189,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.996999979019165,"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":0.8293828368186951},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.7889570593833923},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.7614648342132568},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.7482389211654663},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6768621206283569},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6622275114059448},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.4947797656059265},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47062280774116516},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42418372631073},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4236568808555603},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.18975675106048584},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.16709551215171814},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08744311332702637}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8293828368186951},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7889570593833923},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.7614648342132568},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7482389211654663},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6768621206283569},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6622275114059448},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.4947797656059265},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47062280774116516},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42418372631073},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4236568808555603},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.18975675106048584},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.16709551215171814},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08744311332702637},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip40778.2020.9191007","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9191007","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1514535095","https://openalex.org/W1949049686","https://openalex.org/W1990592195","https://openalex.org/W2092985495","https://openalex.org/W2109616376","https://openalex.org/W2121880036","https://openalex.org/W2128254161","https://openalex.org/W2156936307","https://openalex.org/W2194775991","https://openalex.org/W2256362396","https://openalex.org/W2519481857","https://openalex.org/W2582488595","https://openalex.org/W2779176852","https://openalex.org/W2809287713","https://openalex.org/W2866634454","https://openalex.org/W2884068670","https://openalex.org/W2962754725","https://openalex.org/W2963152299","https://openalex.org/W2963153291","https://openalex.org/W2963306157","https://openalex.org/W2963372104","https://openalex.org/W2963855133","https://openalex.org/W2963928582","https://openalex.org/W2990007814","https://openalex.org/W2991006905","https://openalex.org/W2998249728","https://openalex.org/W3099004229","https://openalex.org/W6630875275","https://openalex.org/W6647720530","https://openalex.org/W6726979445","https://openalex.org/W6753074096","https://openalex.org/W6753755972","https://openalex.org/W6770437327","https://openalex.org/W6771174174"],"related_works":["https://openalex.org/W2560215812","https://openalex.org/W2949601986","https://openalex.org/W2788972299","https://openalex.org/W2498789492","https://openalex.org/W2521347458","https://openalex.org/W2729981612","https://openalex.org/W4233449973","https://openalex.org/W2925692864","https://openalex.org/W2972212393","https://openalex.org/W3088721469"],"abstract_inverted_index":{"Due":[0],"to":[1,78,91,95,104],"its":[2],"ill-posed":[3],"nature,":[4],"single":[5,25],"image":[6,26],"dehazing":[7],"is":[8,89,102],"a":[9,53],"challenging":[10],"problem.":[11],"In":[12,45],"this":[13],"paper,":[14],"we":[15,51],"propose":[16],"an":[17],"end-to-end":[18],"feature":[19,59,86],"aggregation":[20],"attention":[21,33,60,87],"network":[22],"(FAAN)":[23],"for":[24],"dehazing.":[27],"It":[28],"incorporates":[29],"the":[30,48,74,106,110,119,124],"idea":[31],"of":[32,58,113],"mechanism":[34],"and":[35,38,65,133],"residual":[36,67,71],"learning":[37,72],"can":[39],"adaptively":[40],"aggregate":[41],"different":[42],"level":[43],"features.":[44,97],"particular,":[46],"in":[47,130],"proposed":[49,125],"FANN,":[50],"design":[52],"novel":[54],"block":[55],"structure":[56],"consisting":[57],"module,":[61],"smoothed":[62,99],"dilated":[63,100],"convolution":[64,101],"local":[66,70],"learning.":[68],"The":[69,85,98,116],"allows":[73],"less":[75],"useful":[76],"information":[77],"be":[79],"bypassed":[80],"through":[81],"multiple":[82],"skip":[83],"connections.":[84],"module":[88],"designed":[90],"assign":[92],"more":[93],"weight":[94],"important":[96],"adopted":[103],"enlarge":[105],"receptive":[107],"field":[108],"without":[109],"negative":[111],"influence":[112],"gridding":[114],"artifacts.":[115],"experiments":[117],"on":[118],"RESIDE":[120],"dataset":[121],"show":[122],"that":[123],"approach":[126],"acquires":[127],"state-of-the-art":[128],"performance":[129],"both":[131],"qualitative":[132],"quantitative":[134],"measures.":[135]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}