{"id":"https://openalex.org/W7125430136","doi":"https://doi.org/10.48550/arxiv.2601.14741","title":"Enhancing Text-to-Image Generation via End-Edge Collaborative Hybrid Super-Resolution","display_name":"Enhancing Text-to-Image Generation via End-Edge Collaborative Hybrid Super-Resolution","publication_year":2026,"publication_date":"2026-01-21","ids":{"openalex":"https://openalex.org/W7125430136","doi":"https://doi.org/10.48550/arxiv.2601.14741"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2601.14741","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.14741","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2601.14741","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5123622717","display_name":"Chongbin Yi","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yi, Chongbin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123574906","display_name":"Yuxin Liang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang, Yuxin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123608266","display_name":"Ziqi Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Ziqi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5123575187","display_name":"Peng Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Peng","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5123622717"],"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":0.765999972820282,"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":0.765999972820282,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.17350000143051147,"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/T11019","display_name":"Image Enhancement Techniques","score":0.013799999840557575,"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/image-stitching","display_name":"Image stitching","score":0.8291000127792358},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.5490999817848206},{"id":"https://openalex.org/keywords/high-fidelity","display_name":"High fidelity","score":0.5016000270843506},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4636000096797943},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.3946000039577484},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.3686999976634979},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.36649999022483826}],"concepts":[{"id":"https://openalex.org/C29081049","wikidata":"https://www.wikidata.org/wiki/Q1364242","display_name":"Image stitching","level":2,"score":0.8291000127792358},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7562999725341797},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.5490999817848206},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.5016000270843506},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4636000096797943},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4618000090122223},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44359999895095825},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.3946000039577484},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.3686999976634979},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.36649999022483826},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.32339999079704285},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.31200000643730164},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3084000051021576},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3077000081539154},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.3061000108718872},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.29249998927116394},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2784000039100647},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.2605000138282776},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.26030001044273376},{"id":"https://openalex.org/C2778820799","wikidata":"https://www.wikidata.org/wiki/Q3454688","display_name":"Cost reduction","level":2,"score":0.2578999996185303}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2601.14741","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.14741","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2601.14741","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.14741","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"article"},"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":{"Artificial":[0],"Intelligence-Generated":[1],"Content":[2],"(AIGC)":[3],"has":[4],"made":[5],"significant":[6],"strides,":[7],"with":[8,184],"high-resolution":[9,34,171],"text-to-image":[10],"(T2I)":[11],"generation":[12,103],"becoming":[13],"increasingly":[14],"critical":[15],"for":[16,61,149,161],"improving":[17],"users'":[18],"Quality":[19],"of":[20,40,47,57],"Experience":[21],"(QoE).":[22],"Although":[23],"resource-constrained":[24],"edge":[25,123],"computing":[26],"adequately":[27],"supports":[28],"fast":[29],"low-resolution":[30,110],"T2I":[31,102],"generations,":[32],"achieving":[33],"output":[35],"still":[36],"faces":[37],"the":[38,45,55,105,122,166,170],"challenge":[39],"ensuring":[41],"image":[42,62,111,189],"fidelity":[43,82],"at":[44,83,121],"cost":[46],"latency.":[48],"To":[49],"address":[50],"this,":[51],"we":[52,92],"first":[53,107],"investigate":[54],"performance":[56],"super-resolution":[58,119],"(SR)":[59],"methods":[60],"enhancement,":[63],"confirming":[64],"a":[65,84,101,109,134,142,153],"fundamental":[66],"trade-off":[67],"that":[68,175],"lightweight":[69,154],"learning-based":[70,155],"SR":[71,79,137,144,156],"struggles":[72],"to":[73,146,158],"recover":[74],"fine":[75],"details,":[76],"while":[77,186],"diffusion-based":[78,143],"achieves":[80],"higher":[81],"substantial":[85],"computational":[86],"cost.":[87],"Motivated":[88],"by":[89,133,181],"these":[90],"observations,":[91],"propose":[93],"an":[94],"end-edge":[95],"collaborative":[96],"generation-enhancement":[97],"framework.":[98],"Upon":[99],"receiving":[100],"task,":[104],"system":[106,177],"generates":[108],"based":[112],"on":[113],"adaptively":[114],"selected":[115],"denoising":[116],"steps":[117],"and":[118,131,152],"scales":[120],"side,":[124],"which":[125],"is":[126],"then":[127],"partitioned":[128],"into":[129,169],"patches":[130,148,160],"processed":[132],"region-aware":[135],"hybrid":[136],"policy.":[138],"This":[139],"policy":[140],"applies":[141],"model":[145,157],"foreground":[147],"detail":[150],"recovery":[151],"background":[159],"efficient":[162],"upscaling,":[163],"ultimately":[164],"stitching":[165],"enhanced":[167],"ones":[168],"image.":[172],"Experiments":[173],"show":[174],"our":[176],"reduces":[178],"service":[179],"latency":[180],"33%":[182],"compared":[183],"baselines":[185],"maintaining":[187],"competitive":[188],"quality.":[190]},"counts_by_year":[],"updated_date":"2026-01-23T23:24:52.574035","created_date":"2026-01-23T00:00:00"}
