{"id":"https://openalex.org/W7165657119","doi":"https://doi.org/10.48550/arxiv.2606.22353","title":"Interest Entanglement: The Hidden Barrier to Blind Super-Resolution Optimization","display_name":"Interest Entanglement: The Hidden Barrier to Blind Super-Resolution Optimization","publication_year":2026,"publication_date":"2026-06-21","ids":{"openalex":"https://openalex.org/W7165657119","doi":"https://doi.org/10.48550/arxiv.2606.22353"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.22353","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.22353","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.22353","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028517133","display_name":"Junxiong Lin","orcid":"https://orcid.org/0009-0000-9499-9983"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Junxiong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102694825","display_name":"Xinji Mai","orcid":"https://orcid.org/0009-0003-4596-5391"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mai, Xinji","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109331455","display_name":"Qianyu Guo","orcid":"https://orcid.org/0009-0007-2497-2639"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Qianyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139153463","display_name":"Haoran Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Haoran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101426100","display_name":"Zeng Tao","orcid":"https://orcid.org/0009-0006-2998-6709"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tao, Zeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101386245","display_name":"Xuan Tong","orcid":"https://orcid.org/0009-0001-4379-4504"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tong, Xuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139167316","display_name":"Ivy Pan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pan, Ivy","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139168796","display_name":"Wenqiang Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Wenqiang","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":0.8500000238418579,"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":0.8500000238418579,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.12700000405311584,"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":0.006099999882280827,"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/leverage","display_name":"Leverage (statistics)","score":0.7041000127792358},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.6075000166893005},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.5390999913215637},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.4700999855995178},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4505999982357025},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4318000078201294},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4271000027656555},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.42419999837875366}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7041000127792358},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6226000189781189},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.6075000166893005},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5390999913215637},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.4700999855995178},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4505999982357025},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4318000078201294},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42719998955726624},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4271000027656555},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.42419999837875366},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.4180000126361847},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4108999967575073},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40380001068115234},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3303000032901764},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.31360000371932983},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3084000051021576},{"id":"https://openalex.org/C68781425","wikidata":"https://www.wikidata.org/wiki/Q2052203","display_name":"Multi-objective optimization","level":2,"score":0.2930999994277954},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.28529998660087585},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2773999869823456},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.2728999853134155},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.27219998836517334},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.26980000734329224},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.2583000063896179}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.22353","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.22353","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.22353","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.22353","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":"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":{"Fidelity":[0],"and":[1,8,106,110,153,179,190],"perceptual":[2,108],"quality":[3,55],"are":[4,76],"two":[5,63],"inherently":[6],"competing":[7],"conflicting":[9],"objectives":[10,23],"in":[11,41,117],"the":[12,30,52,87,98,103,107,112,126,134,142,168,198],"image":[13],"super-resolution":[14],"(SR)":[15],"task.":[16],"Different":[17],"loss":[18,43],"functions":[19],"focus":[20],"on":[21],"these":[22,62,84],"to":[24,37,78,121,144],"varying":[25],"extents.":[26],"Regression":[27],"losses":[28,50],"enhance":[29],"model's":[31,53],"fidelity":[32],"but":[33,56],"lack":[34],"sufficient":[35],"attention":[36],"high-frequency":[38],"details,":[39],"resulting":[40],"a":[42,70,146,176,186],"of":[44,114,137,200],"fine":[45],"details.":[46],"In":[47],"contrast,":[48],"perception":[49],"improve":[51],"visual":[54],"may":[57],"introduce":[58],"undesirable":[59],"artifacts.":[60],"Balancing":[61],"optimization":[64,139,148],"goals":[65,152],"can":[66],"be":[67],"viewed":[68],"as":[69],"Multi-Objective":[71],"Optimization":[72],"problem.":[73,91],"Existing":[74],"methods":[75],"limited":[77],"cautiously":[79],"adjusting":[80],"weight":[81],"parameters":[82],"between":[83,102,158],"losses,":[85],"overlooking":[86],"underlying":[88],"Interest":[89,115],"Entanglement":[90,116],"To":[92,160],"address":[93],"this":[94],"problem,":[95],"we":[96,124,165],"explore":[97,145],"inherent":[99],"frequency-domain":[100],"conflict":[101],"regression":[104],"objective":[105],"objective,":[109],"analyze":[111],"causes":[113],"SR":[118],"tasks.":[119],"According":[120],"our":[122],"findings,":[123],"propose":[125],"Shared-Feature-Representation":[127],"based":[128],"Super-Resolution":[129],"framework":[130],"(SFR),":[131],"which":[132,171],"decouples":[133],"learning":[135],"process":[136],"different":[138],"objectives,":[140],"allowing":[141],"model":[143],"common":[147],"direction":[149],"for":[150],"both":[151],"achieve":[154],"an":[155],"effective":[156],"balance":[157],"them.":[159],"better":[161],"leverage":[162],"shared":[163],"features,":[164],"also":[166],"proposed":[167],"InfoSqueeze":[169],"module,":[170],"filters":[172],"redundant":[173],"information":[174],"through":[175],"dimensionality":[177],"reduction":[178],"expansion":[180],"process,":[181],"effectively":[182],"transforming":[183],"features":[184],"into":[185],"consistent":[187],"space.":[188],"Quantitative":[189],"qualitative":[191],"experiments":[192],"across":[193],"five":[194],"representative":[195],"datasets":[196],"affirm":[197],"superiority":[199],"SFR.":[201]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-24T00:00:00"}
