{"id":"https://openalex.org/W4400810905","doi":"https://doi.org/10.1109/isie54533.2024.10595792","title":"Reweighting Foveal Visual Representations","display_name":"Reweighting Foveal Visual Representations","publication_year":2024,"publication_date":"2024-06-18","ids":{"openalex":"https://openalex.org/W4400810905","doi":"https://doi.org/10.1109/isie54533.2024.10595792"},"language":"en","primary_location":{"id":"doi:10.1109/isie54533.2024.10595792","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isie54533.2024.10595792","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 33rd International Symposium on Industrial Electronics (ISIE)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057436905","display_name":"Xuan-Thuy Vo","orcid":"https://orcid.org/0000-0002-7411-0697"},"institutions":[{"id":"https://openalex.org/I40542001","display_name":"University of Ulsan","ror":"https://ror.org/02c2f8975","country_code":"KR","type":"education","lineage":["https://openalex.org/I40542001"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Xuan-Thuy Vo","raw_affiliation_strings":["University of Ulsan,Electronic and Computer Engineering,Department of Electrical,Ulsan,South Korea,44610"],"affiliations":[{"raw_affiliation_string":"University of Ulsan,Electronic and Computer Engineering,Department of Electrical,Ulsan,South Korea,44610","institution_ids":["https://openalex.org/I40542001"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079734356","display_name":"Duy-Linh Nguyen","orcid":"https://orcid.org/0000-0001-6184-4133"},"institutions":[{"id":"https://openalex.org/I40542001","display_name":"University of Ulsan","ror":"https://ror.org/02c2f8975","country_code":"KR","type":"education","lineage":["https://openalex.org/I40542001"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Duy-Linh Nguyen","raw_affiliation_strings":["University of Ulsan,Electronic and Computer Engineering,Department of Electrical,Ulsan,South Korea,44610"],"affiliations":[{"raw_affiliation_string":"University of Ulsan,Electronic and Computer Engineering,Department of Electrical,Ulsan,South Korea,44610","institution_ids":["https://openalex.org/I40542001"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010613480","display_name":"Adri Priadana","orcid":"https://orcid.org/0000-0002-1553-7631"},"institutions":[{"id":"https://openalex.org/I40542001","display_name":"University of Ulsan","ror":"https://ror.org/02c2f8975","country_code":"KR","type":"education","lineage":["https://openalex.org/I40542001"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Adri Priadana","raw_affiliation_strings":["University of Ulsan,Electronic and Computer Engineering,Department of Electrical,Ulsan,South Korea,44610"],"affiliations":[{"raw_affiliation_string":"University of Ulsan,Electronic and Computer Engineering,Department of Electrical,Ulsan,South Korea,44610","institution_ids":["https://openalex.org/I40542001"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044448641","display_name":"Kang-Hyun Jo","orcid":"https://orcid.org/0000-0002-4937-7082"},"institutions":[{"id":"https://openalex.org/I40542001","display_name":"University of Ulsan","ror":"https://ror.org/02c2f8975","country_code":"KR","type":"education","lineage":["https://openalex.org/I40542001"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kang-Hyun Jo","raw_affiliation_strings":["University of Ulsan,Electronic and Computer Engineering,Department of Electrical,Ulsan,South Korea,44610"],"affiliations":[{"raw_affiliation_string":"University of Ulsan,Electronic and Computer Engineering,Department of Electrical,Ulsan,South Korea,44610","institution_ids":["https://openalex.org/I40542001"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5057436905"],"corresponding_institution_ids":["https://openalex.org/I40542001"],"apc_list":null,"apc_paid":null,"fwci":1.1351,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.75160705,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10971","display_name":"Olfactory and Sensory Function Studies","score":0.4189000129699707,"subfield":{"id":"https://openalex.org/subfields/2809","display_name":"Sensory Systems"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10971","display_name":"Olfactory and Sensory Function Studies","score":0.4189000129699707,"subfield":{"id":"https://openalex.org/subfields/2809","display_name":"Sensory Systems"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/foveal","display_name":"Foveal","score":0.9218546152114868},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7354869246482849},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4637850522994995},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3577158451080322},{"id":"https://openalex.org/keywords/retinal","display_name":"Retinal","score":0.06757405400276184},{"id":"https://openalex.org/keywords/ophthalmology","display_name":"Ophthalmology","score":0.059132158756256104}],"concepts":[{"id":"https://openalex.org/C30181142","wikidata":"https://www.wikidata.org/wiki/Q865103","display_name":"Foveal","level":3,"score":0.9218546152114868},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7354869246482849},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4637850522994995},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3577158451080322},{"id":"https://openalex.org/C2780827179","wikidata":"https://www.wikidata.org/wiki/Q422001","display_name":"Retinal","level":2,"score":0.06757405400276184},{"id":"https://openalex.org/C118487528","wikidata":"https://www.wikidata.org/wiki/Q161437","display_name":"Ophthalmology","level":1,"score":0.059132158756256104},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isie54533.2024.10595792","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isie54533.2024.10595792","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 33rd International Symposium on Industrial Electronics (ISIE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320311687","display_name":"Ministry of Education","ror":"https://ror.org/03m01yf64"},{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1861492603","https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2507296351","https://openalex.org/W2910628332","https://openalex.org/W2963150697","https://openalex.org/W2963351448","https://openalex.org/W3092663126","https://openalex.org/W3096609285","https://openalex.org/W3131500599","https://openalex.org/W3138516171","https://openalex.org/W3164208409","https://openalex.org/W3175515048","https://openalex.org/W4225829036","https://openalex.org/W4226272139","https://openalex.org/W4226334005","https://openalex.org/W4282968898","https://openalex.org/W4312443924","https://openalex.org/W4312960790","https://openalex.org/W4312986923","https://openalex.org/W4313170858","https://openalex.org/W4379256083","https://openalex.org/W4385245566","https://openalex.org/W4386076539","https://openalex.org/W4388145401","https://openalex.org/W4390872550","https://openalex.org/W4390872693","https://openalex.org/W4402716415","https://openalex.org/W4402727033","https://openalex.org/W4402754177","https://openalex.org/W6620707391","https://openalex.org/W6784333009","https://openalex.org/W6788135285","https://openalex.org/W6795463671","https://openalex.org/W6802648153","https://openalex.org/W6810859482","https://openalex.org/W6839765744","https://openalex.org/W6846181243","https://openalex.org/W6853231579","https://openalex.org/W6860367492"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2775347418","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Biological":[0],"foveal":[1,20,87,190],"vision":[2,21,88],"consists":[3],"of":[4,16,80,131,162],"multiple":[5],"contour":[6],"regions,":[7],"determined":[8],"by":[9,45,58,74,125,143,154,172,201],"the":[10,14,17,28,41,72,81,126,129,132,166,182,187,196,254],"varying":[11],"distances":[12],"from":[13,40,128,137],"center":[15,130],"gaze.":[18],"Adopting":[19],"in":[22,35,67],"deep":[23],"neural":[24],"networks":[25],"can":[26],"have":[27,70],"ability":[29],"to":[30,117,165,180,185,251,261],"capture":[31],"various":[32,119],"visual":[33,68,99,115],"features":[34,79,120,168],"different":[36,122],"regions.":[37,191],"Long-range":[38],"dependencies":[39,55],"gaze":[42],"are":[43,56,141,152,199,209],"modeled":[44,142],"global":[46,78],"operations":[47,60],"(global":[48],"self-attention":[49,62,145],"and":[50,53,63,77,149,216,227,242],"state-space":[51],"model)":[52],"short-range":[54],"perceived":[57,153],"local":[59,76,155],"(local":[61],"convolution).":[64],"Existing":[65],"works":[66],"backbones":[69,263],"improved":[71],"performance":[73],"modeling":[75,98],"input":[82,148],"images.":[83],"However,":[84],"fully":[85],"perceiving":[86],"has":[89],"not":[90],"been":[91],"well":[92],"explored,":[93],"which":[94],"is":[95,169],"crucial":[96],"for":[97,113],"features.":[100],"To":[101],"address":[102],"this":[103,105,194],"issue,":[104],"paper":[106],"proposes":[107],"a":[108,114,173],"Reweighting":[109],"Foveal":[110],"(RF)":[111],"mechanism":[112],"representation":[116],"extract":[118],"at":[121],"regions":[123,136,151],"varied":[124],"distance":[127],"query\u2019s":[133],"position.":[134],"Far":[135],"each":[138,163],"query":[139],"position":[140],"pooling":[144],"on":[146,157,177,193,211],"coarse":[147],"nearest":[150],"convolution":[156],"fine-grained":[158],"input.":[159],"The":[160],"importance":[161],"region":[164],"model":[167,183],"also":[170],"emphasized":[171],"reweighting":[174],"module":[175],"based":[176],"softmax":[178],"attention":[179],"let":[181],"learn":[184],"perceive":[186],"relationship":[188],"among":[189],"Based":[192],"design,":[195],"RF":[197,203,249],"Transformers":[198,250],"introduced":[200],"stacking":[202],"blocks":[204],"across":[205],"stages.":[206],"Extensive":[207],"experiments":[208],"validated":[210],"image":[212,220],"classification,":[213,221],"object":[214],"detection,":[215],"semantic":[217],"segmentation.":[218],"On":[219],"RF-1":[222],"with":[223],"8.5":[224],"M":[225],"parameters":[226],"0.7":[228],"GFLOPs":[229],"achieves":[230],"$\\mathbf{7":[231],"8":[232],".":[233],"2":[234],"\\%}$":[235],"Top-1":[236],"accuracy":[237],"that":[238],"surpasses":[239],"recent":[240,262],"ConvNets":[241],"Vision":[243],"Transformer":[244],"methods.":[245],"When":[246],"transferring":[247],"trained":[248],"other":[252],"tasks,":[253],"proposed":[255],"methods":[256],"obtain":[257],"competitive":[258],"performances":[259],"compared":[260],"while":[264],"getting":[265],"better":[266],"efficiency.":[267]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}
