{"id":"https://openalex.org/W4308235631","doi":"https://doi.org/10.1109/icip46576.2022.9897589","title":"EANET: Efficient Attention-Augmented Network for Real-Time Semantic Segmentation","display_name":"EANET: Efficient Attention-Augmented Network for Real-Time Semantic Segmentation","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4308235631","doi":"https://doi.org/10.1109/icip46576.2022.9897589"},"language":"en","primary_location":{"id":"doi:10.1109/icip46576.2022.9897589","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip46576.2022.9897589","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5102832851","display_name":"Jianan Dong","orcid":"https://orcid.org/0000-0002-3704-7692"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianan Dong","raw_affiliation_strings":["Tianjin University,School of Electrical and Information Engineering,Tianjin,China","School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University,School of Electrical and Information Engineering,Tianjin,China","institution_ids":["https://openalex.org/I162868743"]},{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033014667","display_name":"Jichang Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jichang Guo","raw_affiliation_strings":["Tianjin University,School of Electrical and Information Engineering,Tianjin,China","School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University,School of Electrical and Information Engineering,Tianjin,China","institution_ids":["https://openalex.org/I162868743"]},{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033161342","display_name":"Huihui Yue","orcid":"https://orcid.org/0000-0001-8620-7093"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huihui Yue","raw_affiliation_strings":["Tianjin University,School of Electrical and Information Engineering,Tianjin,China","School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University,School of Electrical and Information Engineering,Tianjin,China","institution_ids":["https://openalex.org/I162868743"]},{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100752932","display_name":"Huan Gao","orcid":"https://orcid.org/0000-0002-2466-5547"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huan Gao","raw_affiliation_strings":["Tianjin University,School of Electrical and Information Engineering,Tianjin,China","School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University,School of Electrical and Information Engineering,Tianjin,China","institution_ids":["https://openalex.org/I162868743"]},{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I162868743"],"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":"28","issue":null,"first_page":"3968","last_page":"3972"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9991000294685364,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9973000288009644,"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/computer-science","display_name":"Computer science","score":0.8622003793716431},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7963071465492249},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.7095476984977722},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6830642819404602},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5752044916152954},{"id":"https://openalex.org/keywords/attention-network","display_name":"Attention network","score":0.46175551414489746},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.44375765323638916},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.43617311120033264},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4316731095314026},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.42085781693458557},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.42045503854751587},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3982348144054413},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.20846974849700928},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.14132827520370483}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8622003793716431},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7963071465492249},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.7095476984977722},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6830642819404602},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5752044916152954},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.46175551414489746},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.44375765323638916},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.43617311120033264},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4316731095314026},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.42085781693458557},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.42045503854751587},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3982348144054413},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.20846974849700928},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.14132827520370483},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip46576.2022.9897589","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip46576.2022.9897589","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7799999713897705,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322701","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1903029394","https://openalex.org/W2194775991","https://openalex.org/W2412782625","https://openalex.org/W2560023338","https://openalex.org/W2762439315","https://openalex.org/W2886934227","https://openalex.org/W2921495890","https://openalex.org/W2928560789","https://openalex.org/W2955058313","https://openalex.org/W2963091558","https://openalex.org/W2963125010","https://openalex.org/W2963418739","https://openalex.org/W2963419596","https://openalex.org/W2963604034","https://openalex.org/W2963890956","https://openalex.org/W2964217532","https://openalex.org/W2981689412","https://openalex.org/W3034958977","https://openalex.org/W3082097505","https://openalex.org/W3108450508","https://openalex.org/W3126719109","https://openalex.org/W3159640305","https://openalex.org/W3181161645","https://openalex.org/W3196904463","https://openalex.org/W4293406525","https://openalex.org/W4297775537","https://openalex.org/W6717372056","https://openalex.org/W6737664043","https://openalex.org/W6790518543"],"related_works":["https://openalex.org/W2624903463","https://openalex.org/W3207051105","https://openalex.org/W2093384100","https://openalex.org/W4386960967","https://openalex.org/W4313452767","https://openalex.org/W2083896825","https://openalex.org/W2802018156","https://openalex.org/W4290774787","https://openalex.org/W3196281958","https://openalex.org/W4293067758"],"abstract_inverted_index":{"Real-time":[0],"semantic":[1],"segmentation":[2],"plays":[3],"a":[4,110,115],"significant":[5],"role":[6],"in":[7],"many":[8],"real-world":[9],"applications.":[10],"However,":[11],"existing":[12],"methods":[13],"usually":[14],"neglect":[15],"the":[16,35,76],"importance":[17],"of":[18,30],"aggregating":[19],"global":[20,67],"scene":[21],"clues":[22],"and":[23,38,92],"multi-level":[24,95],"semantics":[25,91],"due":[26],"to":[27,65,88],"computational":[28],"limits":[29],"mobile":[31],"devices.":[32],"To":[33],"address":[34],"above":[36],"challenges":[37],"maintain":[39],"higher":[40],"accuracy,":[41],"we":[42,51],"propose":[43],"an":[44,54,85],"efficient":[45],"attention-augmented":[46],"network,":[47],"namely":[48],"EANet.":[49],"Specifically,":[50],"first":[52],"leverage":[53],"extremely":[55],"lightweight":[56],"attention":[57,62,80,86],"module":[58,63,82],"called":[59],"sparse":[60],"strip":[61],"(SSAM)":[64],"retain":[66],"contextual":[68],"information":[69],"while":[70],"greatly":[71],"reducing":[72],"computation":[73],"cost.":[74],"Moreover,":[75],"meticulously":[77],"designed":[78],"joint":[79],"fusion":[81],"(JAFM)":[83],"follows":[84],"strategy":[87],"efficiently":[89],"integrate":[90],"details":[93],"from":[94],"features.":[96],"On":[97],"Cityscapes":[98,128],"test":[99],"set,":[100],"our":[101,122],"network":[102],"achieves":[103,124],"74.6%":[104],"mIoU":[105],"at":[106],"35.4":[107],"FPS":[108],"on":[109,127],"single":[111],"GTX1080Ti":[112],"GPU":[113],"with":[114],"1024\u00d72048-pixel":[116],"image.":[117],"Extensive":[118],"experiments":[119],"show":[120],"that":[121],"EANet":[123],"promising":[125],"results":[126],"dataset.":[129]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}