{"id":"https://openalex.org/W4403780775","doi":"https://doi.org/10.1145/3664647.3681682","title":"Enhancing Images with Coupled Low-Resolution and Ultra-Dark Degradations: A Tri-level Learning Framework","display_name":"Enhancing Images with Coupled Low-Resolution and Ultra-Dark Degradations: A Tri-level Learning Framework","publication_year":2024,"publication_date":"2024-10-26","ids":{"openalex":"https://openalex.org/W4403780775","doi":"https://doi.org/10.1145/3664647.3681682"},"language":"en","primary_location":{"id":"doi:10.1145/3664647.3681682","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3664647.3681682","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3664647.3681682?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3664647.3681682?download=true","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101865271","display_name":"Jiaxin Gao","orcid":"https://orcid.org/0000-0002-0023-1269"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiaxin Gao","raw_affiliation_strings":["Dalian University of Technology, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0002-0023-1269","affiliations":[{"raw_affiliation_string":"Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069726992","display_name":"Yaohua Liu","orcid":"https://orcid.org/0000-0002-9057-1645"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaohua Liu","raw_affiliation_strings":["Dalian University of Technology, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0002-9057-1645","affiliations":[{"raw_affiliation_string":"Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101865271"],"corresponding_institution_ids":["https://openalex.org/I27357992"],"apc_list":null,"apc_paid":null,"fwci":0.7142,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.72164307,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"8642","last_page":"8651"},"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/T11105","display_name":"Advanced Image Processing 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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5443860292434692},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4954019784927368},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.4837625026702881},{"id":"https://openalex.org/keywords/low-resolution","display_name":"Low resolution","score":0.47291430830955505},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4568217396736145},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3698843717575073},{"id":"https://openalex.org/keywords/high-resolution","display_name":"High resolution","score":0.3000345230102539},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.22421053051948547},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.11970990896224976}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5443860292434692},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4954019784927368},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.4837625026702881},{"id":"https://openalex.org/C3019883945","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Low resolution","level":3,"score":0.47291430830955505},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4568217396736145},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3698843717575073},{"id":"https://openalex.org/C3020199158","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"High resolution","level":2,"score":0.3000345230102539},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.22421053051948547},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.11970990896224976}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3664647.3681682","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3664647.3681682","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3664647.3681682?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3664647.3681682","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3664647.3681682","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3664647.3681682?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.6499999761581421,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4403780775.pdf","grobid_xml":"https://content.openalex.org/works/W4403780775.grobid-xml"},"referenced_works_count":52,"referenced_works":["https://openalex.org/W569478347","https://openalex.org/W1966068039","https://openalex.org/W1982471090","https://openalex.org/W2102166818","https://openalex.org/W2133665775","https://openalex.org/W2150721269","https://openalex.org/W2164847484","https://openalex.org/W2340897893","https://openalex.org/W2962785568","https://openalex.org/W2963729050","https://openalex.org/W2997894278","https://openalex.org/W3013529009","https://openalex.org/W3034347506","https://openalex.org/W3114677757","https://openalex.org/W3123244552","https://openalex.org/W3123350987","https://openalex.org/W3125869362","https://openalex.org/W3134649899","https://openalex.org/W3157498319","https://openalex.org/W3174883353","https://openalex.org/W3181096156","https://openalex.org/W3202650012","https://openalex.org/W3204374989","https://openalex.org/W3205424528","https://openalex.org/W3214264009","https://openalex.org/W3217287203","https://openalex.org/W4206706211","https://openalex.org/W4213121525","https://openalex.org/W4214849322","https://openalex.org/W4226322264","https://openalex.org/W4285290430","https://openalex.org/W4285600750","https://openalex.org/W4288071427","https://openalex.org/W4321794021","https://openalex.org/W4382240242","https://openalex.org/W4386075513","https://openalex.org/W4386083034","https://openalex.org/W4387696030","https://openalex.org/W4389381404","https://openalex.org/W4390872514","https://openalex.org/W4390872521","https://openalex.org/W4390872882","https://openalex.org/W4390873516","https://openalex.org/W4390873662","https://openalex.org/W4391696928","https://openalex.org/W4392693690","https://openalex.org/W4393147902","https://openalex.org/W4393149622","https://openalex.org/W4393153772","https://openalex.org/W4393158972","https://openalex.org/W4396696493","https://openalex.org/W4401109994"],"related_works":["https://openalex.org/W251433779","https://openalex.org/W2362774332","https://openalex.org/W2037893049","https://openalex.org/W4249245269","https://openalex.org/W2765548132","https://openalex.org/W2025681766","https://openalex.org/W2542402767","https://openalex.org/W3023086044","https://openalex.org/W4212954839","https://openalex.org/W4401570279"],"abstract_inverted_index":{"Due":[0],"to":[1,77,95,125,132,189],"device":[2],"constraints":[3,138],"and":[4,13,19,49,64,92,117,172,175,214,225],"lighting":[5],"conditions,":[6],"captured":[7],"images":[8,23],"frequently":[9],"exhibit":[10],"coupled":[11,97],"low-resolution":[12],"ultra-dark":[14,22,205],"degradations.":[15],"Enhancing":[16],"the":[17,75,87,101,111,121,126,134,145,150,199],"visibility":[18],"resolution":[20],"of":[21,136,149],"simultaneously":[24],"is":[25],"crucial":[26],"for":[27,139],"practical":[28],"applications.":[29],"Current":[30],"approaches":[31],"often":[32],"address":[33,69],"both":[34,140],"tasks":[35,119],"in":[36,58,223,227],"isolation":[37],"or":[38],"through":[39],"simplistic":[40],"cascading":[41],"strategies,":[42],"while":[43],"also":[44],"relying":[45],"heavily":[46],"on":[47],"empirical":[48],"manually":[50],"designed":[51],"composite":[52],"loss":[53],"constraints,":[54],"which":[55,165],"inevitably":[56],"results":[57],"compromised":[59],"training":[60,163],"efficacy,":[61],"increased":[62],"artifacts,":[63],"diminished":[65],"detail":[66,194],"fidelity.":[67],"To":[68],"these":[70],"issues,":[71],"we":[72,109,129,154,179],"propose":[73],"TriCo,":[74],"first":[76],"adopt":[78],"a":[79,156,167],"Tri":[80],"-level":[81],"learning":[82,116,135,141,151],"framework":[83],"that":[84],"explicitly":[85],"formulates":[86],"bidirectional":[88],"Co":[89],"operative":[90],"relationship":[91],"devises":[93],"algorithms":[94],"tackle":[96],"degradation":[98],"factors.":[99],"In":[100],"optimization":[102],"across":[103,203,211],"Upper":[104],"(U)-Middle":[105],"(M)-Lower":[106],"(L)":[107],"levels,":[108,128],"model":[110,187],"synergistic":[112],"dependencies":[113],"between":[114],"illumination":[115,182],"super-resolution":[118],"within":[120],"M-L":[122],"levels.":[123],"Moving":[124],"U-M":[127],"introduce":[130],"hyper-variables":[131],"automate":[133],"beneficial":[137],"tasks,":[142],"moving":[143],"beyond":[144],"traditional":[146],"trial-and-error":[147],"pitfalls":[148],"process.":[152],"Algorithmically,":[153],"establish":[155],"Phased":[157],"Gradient-Response":[158],"(PGR)":[159],"algorithm":[160],"as":[161],"our":[162],"mechanism,":[164],"facilitates":[166],"dynamic,":[168],"inter-variable":[169],"gradient":[170],"feedback":[171],"ensures":[173],"efficient":[174],"rapid":[176],"convergence.":[177],"Moreover,":[178],"merge":[180],"inherent":[181],"priors":[183],"with":[184],"universal":[185],"semantic":[186],"features":[188],"adaptively":[190],"guide":[191],"pixel-level":[192],"high-frequency":[193],"recovery.":[195],"Extensive":[196],"experimentation":[197],"validates":[198],"framework's":[200],"broad":[201],"generalizability":[202],"challenging":[204],"scenarios,":[206],"outperforming":[207],"current":[208],"state-of-the-art":[209],"methods":[210],"4":[212],"real":[213],"synthetic":[215],"benchmark":[216],"datasets":[217],"over":[218],"6":[219],"metrics":[220],"(e.g.,":[221],"5.8%\u2190":[222],"PSNR":[224],"26.6%\u2190":[226],"LPIPS).":[228]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-10T14:07:55.174380","created_date":"2025-10-10T00:00:00"}