{"id":"https://openalex.org/W7168235337","doi":"https://doi.org/10.48550/arxiv.2607.11088","title":"CUST: Clustered Unit-level Similarity Transformer for Lightweight Image Super-Resolution","display_name":"CUST: Clustered Unit-level Similarity Transformer for Lightweight Image Super-Resolution","publication_year":2026,"publication_date":"2026-07-13","ids":{"openalex":"https://openalex.org/W7168235337","doi":"https://doi.org/10.48550/arxiv.2607.11088"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.11088","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.11088","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.2607.11088","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5140578320","display_name":"Jeongsoo Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Kim, Jeongsoo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5140578320"],"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":0.9147999882698059,"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":0.9147999882698059,"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":0.06390000134706497,"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"}},{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.0027000000700354576,"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/memory-footprint","display_name":"Memory footprint","score":0.43779999017715454},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4302000105381012},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.38769999146461487},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.3765999972820282},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.3725999891757965},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37059998512268066},{"id":"https://openalex.org/keywords/offset","display_name":"Offset (computer science)","score":0.35199999809265137},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.33239999413490295}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7663999795913696},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4977000057697296},{"id":"https://openalex.org/C74912251","wikidata":"https://www.wikidata.org/wiki/Q6815727","display_name":"Memory footprint","level":2,"score":0.43779999017715454},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4302000105381012},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.38769999146461487},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.3765999972820282},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.3725999891757965},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37059998512268066},{"id":"https://openalex.org/C175291020","wikidata":"https://www.wikidata.org/wiki/Q1156822","display_name":"Offset (computer science)","level":2,"score":0.35199999809265137},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3337000012397766},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.33239999413490295},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.31619998812675476},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3082999885082245},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.29170000553131104},{"id":"https://openalex.org/C64754055","wikidata":"https://www.wikidata.org/wiki/Q7574053","display_name":"Spatial contextual awareness","level":2,"score":0.28690001368522644},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.27950000762939453},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.2793000042438507},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.27379998564720154},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2671999931335449},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.2565000057220459},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.25459998846054077}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.11088","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.11088","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.2607.11088","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.11088","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":[{"display_name":"Sustainable cities and communities","score":0.5986489653587341,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recently,":[0],"Vision":[1],"Transformer":[2,71],"(ViT)-based":[3],"models":[4,171],"have":[5,43],"exhibited":[6],"remarkable":[7],"performance":[8],"in":[9],"image":[10],"super-resolution.":[11],"However,":[12],"the":[13,50,56,67,126,130],"quadratic":[14],"computational":[15,149],"complexity":[16],"of":[17,59],"ViTs":[18],"with":[19],"respect":[20],"to":[21,29,88,92,115,165],"spatial":[22],"resolution":[23],"severely":[24],"constrains":[25],"their":[26,134],"efficiency,":[27],"leading":[28],"high":[30],"latency":[31],"and":[32,80,90,133,151,160],"massive":[33],"memory":[34,158],"consumption.":[35],"To":[36,61],"alleviate":[37],"this,":[38],"various":[39],"window-based":[40],"attention":[41,113],"mechanisms":[42],"been":[44],"proposed;":[45],"yet,":[46],"they":[47],"inherently":[48],"compromise":[49],"long-range":[51],"dependency":[52],"modeling":[53],"that":[54,76,140],"is":[55,176],"primary":[57],"advantage":[58],"ViTs.":[60],"overcome":[62],"these":[63],"limitations,":[64],"we":[65],"propose":[66],"Clustered":[68],"Unit-level":[69],"Similarity":[70],"(CUST),":[72],"a":[73,96,145,156],"novel":[74],"architecture":[75],"efficiently":[77],"integrates":[78],"global":[79,167],"local":[81,102,117],"information.":[82],"Specifically,":[83],"CUST":[84],"enables":[85],"each":[86],"patch":[87],"aggregate":[89],"attend":[91],"similar":[93],"patches":[94],"within":[95],"broadened":[97],"regional":[98],"scope":[99],"outside":[100],"its":[101],"window,":[103],"thereby":[104],"capturing":[105],"extensive":[106],"contextual":[107],"understanding.":[108],"Furthermore,":[109],"it":[110],"employs":[111],"overlapping":[112],"windows":[114],"capture":[116],"dependencies,":[118],"while":[119],"explicitly":[120],"extracting":[121],"high-frequency":[122],"details":[123],"by":[124],"computing":[125],"residual":[127],"difference":[128],"between":[129,148],"original":[131],"features":[132],"downsampled-upsampled":[135],"counterparts.":[136],"Comprehensive":[137],"experiments":[138],"demonstrate":[139],"our":[141],"proposed":[142],"model":[143],"achieves":[144,155],"practical":[146],"balance":[147],"efficiency":[150],"restoration":[152],"performance.":[153],"It":[154],"lower":[157],"footprint":[159],"faster":[161],"inference":[162],"speed":[163],"compared":[164],"recent":[166],"context":[168],"or":[169],"lightweight":[170],"under":[172],"realistic":[173],"constraints.":[174],"Code":[175],"available":[177],"at":[178],"[https://github.com/jwgdmkj/CUST].":[179]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-15T00:00:00"}