{"id":"https://openalex.org/W7153273496","doi":"https://doi.org/10.48550/arxiv.2604.07994","title":"SAT: Selective Aggregation Transformer for Image Super-Resolution","display_name":"SAT: Selective Aggregation Transformer for Image Super-Resolution","publication_year":2026,"publication_date":"2026-04-09","ids":{"openalex":"https://openalex.org/W7153273496","doi":"https://doi.org/10.48550/arxiv.2604.07994"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.07994","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.07994","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.07994","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120704304","display_name":"Dinh Phu Tran","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tran, Dinh Phu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133392549","display_name":"Thao Do","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Do, Thao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079428602","display_name":"Saad Wazir","orcid":"https://orcid.org/0000-0001-9260-1636"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wazir, Saad","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133326135","display_name":"Seongah Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Seongah","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046006067","display_name":"Seon Kwon Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Seon Kwon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133331715","display_name":"Daeyoung Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Daeyoung","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9725000262260437,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9725000262260437,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.00570000009611249,"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":0.0032999999821186066,"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/computational-complexity-theory","display_name":"Computational complexity theory","score":0.6098999977111816},{"id":"https://openalex.org/keywords/flops","display_name":"FLOPS","score":0.5220999717712402},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.47189998626708984},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.43369999527931213},{"id":"https://openalex.org/keywords/quadratic-equation","display_name":"Quadratic equation","score":0.3928999900817871},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.37940001487731934},{"id":"https://openalex.org/keywords/time-complexity","display_name":"Time complexity","score":0.3122999966144562}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6588000059127808},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.6098999977111816},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.5220999717712402},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.47189998626708984},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4429999887943268},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.43369999527931213},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.3928999900817871},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.37940001487731934},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.3122999966144562},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.3091000020503998},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.30820000171661377},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3043000102043152},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.29919999837875366},{"id":"https://openalex.org/C90702460","wikidata":"https://www.wikidata.org/wiki/Q1055112","display_name":"Circuit complexity","level":3,"score":0.27799999713897705},{"id":"https://openalex.org/C81845259","wikidata":"https://www.wikidata.org/wiki/Q290117","display_name":"Quadratic programming","level":2,"score":0.2720000147819519},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.267300009727478},{"id":"https://openalex.org/C127964446","wikidata":"https://www.wikidata.org/wiki/Q1092142","display_name":"Computational resource","level":3,"score":0.259799987077713}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.07994","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.07994","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.07994","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.07994","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Transformer-based":[0],"approaches":[1],"have":[2],"revolutionized":[3],"image":[4],"super-resolution":[5],"by":[6,38,72,82,152,165],"modeling":[7],"long-range":[8,63],"dependencies.":[9],"However,":[10],"the":[11,78,92,96,148,157],"quadratic":[12],"computational":[13,103],"complexity":[14,108],"of":[15,80,95,160],"vanilla":[16],"self-attention":[17],"mechanisms":[18],"poses":[19],"significant":[20],"challenges,":[21],"often":[22,43],"leading":[23,65],"to":[24,66,134,154,167],"compromises":[25],"between":[26],"efficiency":[27],"and":[28,109,120,131],"global":[29,112],"context":[30],"exploitation.":[31],"Recent":[32],"window-based":[33],"attention":[34],"methods":[35],"mitigate":[36,49],"this":[37],"localizing":[39],"computations,":[40],"but":[41],"they":[42],"yield":[44],"restricted":[45],"receptive":[46,70],"fields.":[47],"To":[48],"these":[50],"limitations,":[51],"we":[52],"propose":[53],"Selective":[54],"Aggregation":[55,88],"Transformer":[56],"(SAT).":[57],"This":[58,99],"novel":[59],"transformer":[60],"efficiently":[61],"captures":[62],"dependencies,":[64],"an":[67],"enlarged":[68],"model":[69],"field":[71],"selectively":[73],"aggregating":[74],"key-value":[75],"matrices":[76],"(reducing":[77],"number":[79,159],"tokens":[81],"97\\%)":[83],"via":[84],"our":[85],"Density-driven":[86],"Token":[87],"algorithm":[89],"while":[90,156],"maintaining":[91],"full":[93],"resolution":[94],"query":[97],"matrix.":[98],"design":[100],"significantly":[101],"reduces":[102],"costs,":[104],"resulting":[105],"in":[106],"lower":[107],"enabling":[110],"scalable":[111],"interactions":[113],"without":[114],"compromising":[115],"reconstruction":[116],"fidelity.":[117],"SAT":[118,146],"identifies":[119],"represents":[121],"each":[122],"cluster":[123],"with":[124],"a":[125],"single":[126],"aggregation":[127],"token,":[128],"utilizing":[129],"density":[130],"isolation":[132],"metrics":[133],"ensure":[135],"that":[136,145],"critical":[137],"high-frequency":[138],"details":[139],"are":[140],"preserved.":[141],"Experimental":[142],"results":[143],"demonstrate":[144],"outperforms":[147],"state-of-the-art":[149],"method":[150],"PFT":[151],"up":[153,166],"0.22dB,":[155],"total":[158],"FLOPs":[161],"can":[162],"be":[163],"reduced":[164],"27\\%.":[168]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-11T00:00:00"}
