{"id":"https://openalex.org/W4387696440","doi":"https://doi.org/10.3390/s23208507","title":"Deep Learning Tone-Mapping and Demosaicing for Automotive Vision Systems","display_name":"Deep Learning Tone-Mapping and Demosaicing for Automotive Vision Systems","publication_year":2023,"publication_date":"2023-10-17","ids":{"openalex":"https://openalex.org/W4387696440","doi":"https://doi.org/10.3390/s23208507","pmid":"https://pubmed.ncbi.nlm.nih.gov/37896600"},"language":"en","primary_location":{"id":"doi:10.3390/s23208507","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23208507","pdf_url":"https://www.mdpi.com/1424-8220/23/20/8507/pdf?version=1697511612","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/23/20/8507/pdf?version=1697511612","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074330398","display_name":"Ana Stojkovi\u0107","orcid":"https://orcid.org/0000-0001-9087-1798"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":true,"raw_author_name":"Ana Stojkovic","raw_affiliation_strings":["IMEC, IPI (Image Processing and Interpretation), Ghent University, 9000 Ghent, Belgium"],"raw_orcid":"https://orcid.org/0000-0001-9087-1798","affiliations":[{"raw_affiliation_string":"IMEC, IPI (Image Processing and Interpretation), Ghent University, 9000 Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040156949","display_name":"Jan Aelterman","orcid":"https://orcid.org/0000-0002-5543-2631"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":true,"raw_author_name":"Jan Aelterman","raw_affiliation_strings":["IMEC, IPI (Image Processing and Interpretation), Ghent University, 9000 Ghent, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IMEC, IPI (Image Processing and Interpretation), Ghent University, 9000 Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063442720","display_name":"David Van Hamme","orcid":"https://orcid.org/0000-0003-2112-3475"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"David Van Hamme","raw_affiliation_strings":["IMEC, IPI (Image Processing and Interpretation), Ghent University, 9000 Ghent, Belgium"],"raw_orcid":"https://orcid.org/0000-0003-2112-3475","affiliations":[{"raw_affiliation_string":"IMEC, IPI (Image Processing and Interpretation), Ghent University, 9000 Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000959943","display_name":"Ivana Shopovska","orcid":"https://orcid.org/0000-0002-8487-9598"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Ivana Shopovska","raw_affiliation_strings":["IMEC, IPI (Image Processing and Interpretation), Ghent University, 9000 Ghent, Belgium"],"raw_orcid":"https://orcid.org/0000-0002-8487-9598","affiliations":[{"raw_affiliation_string":"IMEC, IPI (Image Processing and Interpretation), Ghent University, 9000 Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071483672","display_name":"Wilfried Philips","orcid":"https://orcid.org/0000-0003-4456-4353"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Wilfried Philips","raw_affiliation_strings":["IMEC, IPI (Image Processing and Interpretation), Ghent University, 9000 Ghent, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IMEC, IPI (Image Processing and Interpretation), Ghent University, 9000 Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5040156949","https://openalex.org/A5074330398"],"corresponding_institution_ids":["https://openalex.org/I32597200"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":0.3908,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.55755959,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"23","issue":"20","first_page":"8507","last_page":"8507"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9970999956130981,"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/T11666","display_name":"Color Science and Applications","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/tone-mapping","display_name":"Tone mapping","score":0.8469032049179077},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7715843915939331},{"id":"https://openalex.org/keywords/high-dynamic-range","display_name":"High dynamic range","score":0.7222479581832886},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6794055700302124},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6757568717002869},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5941652059555054},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.519136369228363},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5130454301834106},{"id":"https://openalex.org/keywords/demosaicing","display_name":"Demosaicing","score":0.5078755021095276},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.48105573654174805},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4303589463233948},{"id":"https://openalex.org/keywords/dynamic-range","display_name":"Dynamic range","score":0.37688449025154114},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.280700147151947},{"id":"https://openalex.org/keywords/color-image","display_name":"Color image","score":0.2334011197090149},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.189937025308609},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.15802454948425293}],"concepts":[{"id":"https://openalex.org/C8641274","wikidata":"https://www.wikidata.org/wiki/Q1030958","display_name":"Tone mapping","level":4,"score":0.8469032049179077},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7715843915939331},{"id":"https://openalex.org/C2780056265","wikidata":"https://www.wikidata.org/wiki/Q106239881","display_name":"High dynamic range","level":3,"score":0.7222479581832886},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6794055700302124},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6757568717002869},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5941652059555054},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.519136369228363},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5130454301834106},{"id":"https://openalex.org/C27624317","wikidata":"https://www.wikidata.org/wiki/Q263499","display_name":"Demosaicing","level":5,"score":0.5078755021095276},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.48105573654174805},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4303589463233948},{"id":"https://openalex.org/C87133666","wikidata":"https://www.wikidata.org/wiki/Q1161699","display_name":"Dynamic range","level":2,"score":0.37688449025154114},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.280700147151947},{"id":"https://openalex.org/C142616399","wikidata":"https://www.wikidata.org/wiki/Q5148604","display_name":"Color image","level":4,"score":0.2334011197090149},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.189937025308609},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.15802454948425293},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s23208507","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23208507","pdf_url":"https://www.mdpi.com/1424-8220/23/20/8507/pdf?version=1697511612","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:37896600","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37896600","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:10611084","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10611084","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10611084/pdf/sensors-23-08507.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:archive.ugent.be:01HEDXHQ6075K1XB8NMZEGWVBZ","is_oa":true,"landing_page_url":"http://hdl.handle.net/1854/LU-01HEDXHQ6075K1XB8NMZEGWVBZ","pdf_url":null,"source":{"id":"https://openalex.org/S4306400478","display_name":"Ghent University Academic Bibliography (Ghent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I32597200","host_organization_name":"Ghent University","host_organization_lineage":["https://openalex.org/I32597200"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISSN: 1424-8220","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:doaj.org/article:65ab417d052746099670f43042415e6c","is_oa":true,"landing_page_url":"https://doaj.org/article/65ab417d052746099670f43042415e6c","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 23, Iss 20, p 8507 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/s23208507","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23208507","pdf_url":"https://www.mdpi.com/1424-8220/23/20/8507/pdf?version=1697511612","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4387696440.pdf"},"referenced_works_count":70,"referenced_works":["https://openalex.org/W1568014703","https://openalex.org/W1976689962","https://openalex.org/W1998983504","https://openalex.org/W2008346065","https://openalex.org/W2023292900","https://openalex.org/W2035192779","https://openalex.org/W2039830633","https://openalex.org/W2056016381","https://openalex.org/W2071927195","https://openalex.org/W2080258428","https://openalex.org/W2082136663","https://openalex.org/W2086375115","https://openalex.org/W2106111212","https://openalex.org/W2115405325","https://openalex.org/W2116057693","https://openalex.org/W2116197772","https://openalex.org/W2119565138","https://openalex.org/W2130394175","https://openalex.org/W2141957843","https://openalex.org/W2148912807","https://openalex.org/W2153377815","https://openalex.org/W2163239818","https://openalex.org/W2164716550","https://openalex.org/W2170288257","https://openalex.org/W2240434622","https://openalex.org/W2242047952","https://openalex.org/W2244684328","https://openalex.org/W2295904998","https://openalex.org/W2296391911","https://openalex.org/W2510900399","https://openalex.org/W2556872594","https://openalex.org/W2569004391","https://openalex.org/W2608634979","https://openalex.org/W2746556728","https://openalex.org/W2773272881","https://openalex.org/W2792806930","https://openalex.org/W2887850625","https://openalex.org/W2890691497","https://openalex.org/W2921595853","https://openalex.org/W2963400025","https://openalex.org/W2964076515","https://openalex.org/W2972296998","https://openalex.org/W2991399532","https://openalex.org/W3027333448","https://openalex.org/W3035496815","https://openalex.org/W3035564946","https://openalex.org/W3045416071","https://openalex.org/W3123187387","https://openalex.org/W3135318750","https://openalex.org/W3140320287","https://openalex.org/W3140715649","https://openalex.org/W3165506273","https://openalex.org/W3184597591","https://openalex.org/W3190470001","https://openalex.org/W3202784810","https://openalex.org/W3207137934","https://openalex.org/W3215519494","https://openalex.org/W4210936055","https://openalex.org/W4213232514","https://openalex.org/W4238180704","https://openalex.org/W4247218844","https://openalex.org/W4255940437","https://openalex.org/W4283810745","https://openalex.org/W4360605076","https://openalex.org/W4381660703","https://openalex.org/W4382363976","https://openalex.org/W6674427960","https://openalex.org/W6736498762","https://openalex.org/W6792374549","https://openalex.org/W6802767884"],"related_works":["https://openalex.org/W2884377208","https://openalex.org/W2014689642","https://openalex.org/W2410869481","https://openalex.org/W2028994033","https://openalex.org/W1939253538","https://openalex.org/W1993867686","https://openalex.org/W2162796060","https://openalex.org/W2063779402","https://openalex.org/W2065738242","https://openalex.org/W2808832379"],"abstract_inverted_index":{"High":[0],"dynamic":[1,244],"range":[2,245],"(HDR)":[3,45],"imaging":[4,68],"technology":[5],"is":[6,36,57,177,223,251,257,280],"increasingly":[7],"being":[8],"used":[9],"in":[10,22,27,40,55,65,74,91,119,231,248,313],"automated":[11],"driving":[12],"systems":[13],"(ADS)":[14],"for":[15,117,259],"improving":[16],"the":[17,75,206,226,232,239,242,260,264,274,306,328],"safety":[18],"of":[19,32,82,228,241,266],"traffic":[20],"participants":[21],"scenes":[23],"with":[24,38,52,182,197,213,282,294,327],"strong":[25],"differences":[26],"illumination.":[28],"Therefore,":[29],"a":[30,89,127,201,217,269],"combination":[31],"HDR":[33,67,120,155,203,219],"video,":[34],"that":[35,49,149,238,258,292,305],"video":[37],"details":[39],"all":[41],"illumination":[42,56],"regimes,":[43],"and":[44,70,99,140,189,211,277,317,324,331],"object":[46,71,93,170,286,314],"perception":[47],"techniques":[48],"can":[50],"deal":[51],"this":[53,136],"variety":[54],"highly":[58],"desirable.":[59],"Although":[60],"progress":[61],"has":[62,86],"been":[63],"made":[64],"both":[66,321],"solutions":[69],"detection":[72,94,171,287,315],"algorithms":[73,95,113],"recent":[76],"years,":[77],"they":[78],"have":[79,310],"progressed":[80],"independently":[81],"each":[83],"other.":[84],"This":[85,110],"led":[87],"to":[88,102,126,162,178,224,263,284],"situation":[90],"which":[92,123],"are":[96],"typically":[97],"designed":[98],"constantly":[100],"improved":[101],"operate":[103],"on":[104,168,200,216,289],"8":[105],"bit":[106,153],"per":[107,133],"channel":[108],"content.":[109],"makes":[111],"these":[112],"not":[114],"ideally":[115],"suited":[116],"use":[118],"data":[121],"processing,":[122],"natively":[124],"encodes":[125],"higher":[128],"bit-depth":[129],"(12":[130],"bits/16":[131],"bits":[132],"channel).":[134],"In":[135],"paper,":[137],"we":[138],"present":[139],"evaluate":[141],"two":[142,307],"novel":[143],"convolutional":[144],"neural":[145],"network":[146],"(CNN)":[147],"architectures":[148],"intelligently":[150],"convert":[151],"high":[152],"depth":[154],"images":[156],"into":[157],"8-bit":[158,234],"images.":[159],"We":[160],"attempt":[161],"optimize":[163],"reconstruction":[164],"quality":[165],"by":[166,184],"focusing":[167],"ADS":[169,285],"quality.":[172],"The":[173,192,221,253,301],"first":[174,193,261],"research":[175,255],"novelty":[176,256],"jointly":[179],"perform":[180],"tone-mapping":[181,196,212,276,330],"demosaicing":[183,190,210,278,332],"additionally":[185],"successfully":[186],"suppressing":[187],"noise":[188,198,214],"artifacts.":[191],"CNN":[194],"performs":[195,208],"suppression":[199,215],"full-color":[202],"input,":[204],"while":[205,236],"second":[207,254],"joint":[209],"raw":[218],"input.":[220],"focus":[222],"increase":[225],"detectability":[227],"traffic-related":[229,290],"objects":[230],"reconstructed":[233],"content,":[235],"ensuring":[237],"realism":[240],"standard":[243],"(SDR)":[246],"content":[247,291,323,325],"diverse":[249,295],"conditions":[250],"preserved.":[252],"time,":[262],"best":[265],"our":[267],"knowledge,":[268],"thorough":[270],"comparative":[271],"analysis":[272],"against":[273],"state-of-the-art":[275,329],"methods":[279],"performed":[281],"respect":[283],"accuracy":[288,316],"abounds":[293],"challenging":[296],"(i.e.,":[297],"boundary":[298],"cases)":[299],"scenes.":[300],"evaluation":[302],"results":[303],"show":[304],"proposed":[308],"networks":[309],"better":[311],"performance":[312],"image":[318],"quality,":[319],"than":[320],"SDR":[322],"obtained":[326],"algorithms.":[333]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}