{"id":"https://openalex.org/W4385484719","doi":"https://doi.org/10.1109/ijcnn54540.2023.10191491","title":"High Dynamic Range Imaging with Context-aware Transformer","display_name":"High Dynamic Range Imaging with Context-aware Transformer","publication_year":2023,"publication_date":"2023-06-18","ids":{"openalex":"https://openalex.org/W4385484719","doi":"https://doi.org/10.1109/ijcnn54540.2023.10191491"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn54540.2023.10191491","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn54540.2023.10191491","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Joint Conference on Neural Networks (IJCNN)","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/A5100736735","display_name":"Fangfang Zhou","orcid":"https://orcid.org/0009-0002-3264-2182"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fangfang Zhou","raw_affiliation_strings":["Senslab Technology Co., Ltd.,Shanghai,China","Senslab Technology Co., Ltd., Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Senslab Technology Co., Ltd.,Shanghai,China","institution_ids":[]},{"raw_affiliation_string":"Senslab Technology Co., Ltd., Shanghai, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065240694","display_name":"Zhengming Fu","orcid":null},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhengming Fu","raw_affiliation_strings":["NeuroSens Technology,Austin,U.S","NeuroSens Technology, Austin, U.S"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NeuroSens Technology,Austin,U.S","institution_ids":["https://openalex.org/I86519309"]},{"raw_affiliation_string":"NeuroSens Technology, Austin, U.S","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100455987","display_name":"Dan Zhang","orcid":"https://orcid.org/0000-0001-5625-8615"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dan Zhang","raw_affiliation_strings":["Senslab Technology Co., Ltd.,Shanghai,China","Senslab Technology Co., Ltd., Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Senslab Technology Co., Ltd.,Shanghai,China","institution_ids":[]},{"raw_affiliation_string":"Senslab Technology Co., Ltd., Shanghai, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":null,"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":0.9998999834060669,"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/T10531","display_name":"Advanced Vision and Imaging","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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9991000294685364,"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":0.7359668016433716},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7149301767349243},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.6050429344177246},{"id":"https://openalex.org/keywords/high-dynamic-range","display_name":"High dynamic range","score":0.6038474440574646},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.567567765712738},{"id":"https://openalex.org/keywords/high-dynamic-range-imaging","display_name":"High-dynamic-range imaging","score":0.5402393937110901},{"id":"https://openalex.org/keywords/deblurring","display_name":"Deblurring","score":0.4794827401638031},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4793011248111725},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4108502268791199},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3955787420272827},{"id":"https://openalex.org/keywords/dynamic-range","display_name":"Dynamic range","score":0.27686598896980286},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.21070918440818787},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.20100530982017517},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.16106221079826355},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1021776795387268},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.07102322578430176}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7359668016433716},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7149301767349243},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6050429344177246},{"id":"https://openalex.org/C2780056265","wikidata":"https://www.wikidata.org/wiki/Q106239881","display_name":"High dynamic range","level":3,"score":0.6038474440574646},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.567567765712738},{"id":"https://openalex.org/C2781399445","wikidata":"https://www.wikidata.org/wiki/Q309254","display_name":"High-dynamic-range imaging","level":4,"score":0.5402393937110901},{"id":"https://openalex.org/C2777693668","wikidata":"https://www.wikidata.org/wiki/Q25053743","display_name":"Deblurring","level":5,"score":0.4794827401638031},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4793011248111725},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4108502268791199},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3955787420272827},{"id":"https://openalex.org/C87133666","wikidata":"https://www.wikidata.org/wiki/Q1161699","display_name":"Dynamic range","level":2,"score":0.27686598896980286},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.21070918440818787},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.20100530982017517},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.16106221079826355},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1021776795387268},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.07102322578430176},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn54540.2023.10191491","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn54540.2023.10191491","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 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":51,"referenced_works":["https://openalex.org/W55661325","https://openalex.org/W1505723240","https://openalex.org/W1908433443","https://openalex.org/W1991659632","https://openalex.org/W1995813543","https://openalex.org/W2013980527","https://openalex.org/W2015908134","https://openalex.org/W2054927225","https://openalex.org/W2074172223","https://openalex.org/W2110285966","https://openalex.org/W2130724993","https://openalex.org/W2138893600","https://openalex.org/W2147253850","https://openalex.org/W2147743564","https://openalex.org/W2163710755","https://openalex.org/W2397465079","https://openalex.org/W2519006193","https://openalex.org/W2736611505","https://openalex.org/W2766497195","https://openalex.org/W2792476095","https://openalex.org/W2883566908","https://openalex.org/W2894939846","https://openalex.org/W2938390807","https://openalex.org/W2963728414","https://openalex.org/W3006487162","https://openalex.org/W3040184427","https://openalex.org/W3094502228","https://openalex.org/W3108109496","https://openalex.org/W3122099796","https://openalex.org/W3137432642","https://openalex.org/W3138516171","https://openalex.org/W3142504410","https://openalex.org/W3164024107","https://openalex.org/W3173755231","https://openalex.org/W3180123900","https://openalex.org/W3207918547","https://openalex.org/W4211248027","https://openalex.org/W4213038823","https://openalex.org/W4223560357","https://openalex.org/W4290466588","https://openalex.org/W4295832403","https://openalex.org/W4312574643","https://openalex.org/W4319300205","https://openalex.org/W4319878654","https://openalex.org/W4362655725","https://openalex.org/W4385804839","https://openalex.org/W6602205340","https://openalex.org/W6630252119","https://openalex.org/W6749158859","https://openalex.org/W6752825758","https://openalex.org/W6786213788"],"related_works":["https://openalex.org/W2019508106","https://openalex.org/W2152030049","https://openalex.org/W3182707942","https://openalex.org/W2014689642","https://openalex.org/W2036724498","https://openalex.org/W2236339108","https://openalex.org/W1978234925","https://openalex.org/W2884377208","https://openalex.org/W3123618386","https://openalex.org/W1527870538"],"abstract_inverted_index":{"Avoiding":[0],"the":[1,37,57,63,67,73,84,87,132,136,142,152,158,162,168,176,187,197],"introduction":[2],"of":[3,56,89],"ghosts":[4],"when":[5],"synthesising":[6],"LDR":[7,38,133,137],"images":[8,14,39,107],"as":[9],"high":[10],"dynamic":[11],"range":[12],"(HDR)":[13],"is":[15,181],"a":[16,97,120],"challenging":[17,33],"task.":[18],"Convolutional":[19],"neural":[20],"networks":[21],"(CNNs)":[22],"are":[23,32,42,70,81,139,155,165],"effective":[24],"for":[25,103],"HDR":[26,105,179,202],"ghost":[27,177,203],"removal":[28,204],"in":[29],"general,":[30],"but":[31],"to":[34,72,83,127,141],"deal":[35],"with":[36,76,123,172],"if":[40],"there":[41],"large":[43],"movements":[44],"or":[45],"oversaturation/undersaturation.":[46],"Existing":[47],"dual-branch":[48],"methods":[49],"combining":[50],"CNN":[51],"and":[52,86,113],"Transformer":[53,101,145,150],"omit":[54],"part":[55],"information":[58],"from":[59,130],"non-reference":[60],"images,":[61],"while":[62,161],"features":[64,112,115,129,138,154],"extracted":[65,156,166],"by":[66,157,183],"CNN-based":[68,121],"branch":[69],"bound":[71],"kernel":[74],"size":[75],"small":[77],"receptive":[78],"field,":[79],"which":[80,109],"detrimental":[82],"deblurring":[85],"recovery":[88],"oversaturated/undersaturated":[90],"regions.":[91],"In":[92,147],"this":[93],"paper,":[94],"we":[95,118],"propose":[96],"novel":[98],"hierarchical":[99],"dual":[100],"method":[102],"ghost-free":[104],"(HDT-HDR)":[106],"generation,":[108],"extracts":[110],"global":[111,153],"local":[114,163],"simultaneously.":[116],"First,":[117],"use":[119],"head":[122],"spatial":[124],"attention":[125,170],"mechanisms":[126],"extract":[128],"all":[131],"images.":[134],"Second,":[135],"delivered":[140],"Hierarchical":[143],"Dual":[144,149],"(HDT).":[146],"each":[148],"(DT),":[151],"window-based":[159],"Transformer,":[160],"details":[164],"using":[167],"channel":[169],"mechanism":[171],"deformable":[173],"CNNs.":[174],"Finally,":[175],"free":[178],"image":[180],"obtained":[182],"dimensional":[184],"mapping":[185],"on":[186],"HDT":[188],"output.":[189],"Abundant":[190],"experiments":[191],"demonstrate":[192],"that":[193],"our":[194],"HDT-HDR":[195],"achieves":[196],"state-of-the-art":[198],"performance":[199],"among":[200],"existing":[201],"methods.":[205]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":4}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}