{"id":"https://openalex.org/W3161332183","doi":"https://doi.org/10.1109/icpr48806.2021.9413176","title":"Fast and Accurate Real-Time Semantic Segmentation with Dilated Asymmetric Convolutions","display_name":"Fast and Accurate Real-Time Semantic Segmentation with Dilated Asymmetric Convolutions","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3161332183","doi":"https://doi.org/10.1109/icpr48806.2021.9413176","mag":"3161332183"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9413176","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9413176","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","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/A5056502006","display_name":"Leonel Rosas-Arias","orcid":"https://orcid.org/0000-0002-2007-0087"},"institutions":[{"id":"https://openalex.org/I59361560","display_name":"Instituto Polit\u00e9cnico Nacional","ror":"https://ror.org/059sp8j34","country_code":"MX","type":"education","lineage":["https://openalex.org/I59361560"]}],"countries":["MX"],"is_corresponding":true,"raw_author_name":"Leonel Rosas-Arias","raw_affiliation_strings":["Instituto Politecnico Nacional, ESIME Culhuacan, Mexico City, Mexico"],"affiliations":[{"raw_affiliation_string":"Instituto Politecnico Nacional, ESIME Culhuacan, Mexico City, Mexico","institution_ids":["https://openalex.org/I59361560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082384142","display_name":"Gibran Ben\u00edtez-Garc\u00eda","orcid":"https://orcid.org/0000-0003-4945-8314"},"institutions":[{"id":"https://openalex.org/I20529979","display_name":"University of Electro-Communications","ror":"https://ror.org/02x73b849","country_code":"JP","type":"education","lineage":["https://openalex.org/I20529979"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Gibran Benitez-Garcia","raw_affiliation_strings":["The University of Electro-Communications, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"The University of Electro-Communications, Tokyo, Japan","institution_ids":["https://openalex.org/I20529979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012597502","display_name":"Jos\u00e9 Portillo-Portillo","orcid":"https://orcid.org/0000-0001-8863-7804"},"institutions":[{"id":"https://openalex.org/I59361560","display_name":"Instituto Polit\u00e9cnico Nacional","ror":"https://ror.org/059sp8j34","country_code":"MX","type":"education","lineage":["https://openalex.org/I59361560"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Jose Portillo-Portillo","raw_affiliation_strings":["Instituto Politecnico Nacional, ESIME Culhuacan, Mexico City, Mexico"],"affiliations":[{"raw_affiliation_string":"Instituto Politecnico Nacional, ESIME Culhuacan, Mexico City, Mexico","institution_ids":["https://openalex.org/I59361560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041174661","display_name":"Gabriel Sanchez-Perez","orcid":"https://orcid.org/0000-0002-4735-205X"},"institutions":[{"id":"https://openalex.org/I59361560","display_name":"Instituto Polit\u00e9cnico Nacional","ror":"https://ror.org/059sp8j34","country_code":"MX","type":"education","lineage":["https://openalex.org/I59361560"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Gabriel Sanchez-Perez","raw_affiliation_strings":["Instituto Politecnico Nacional, ESIME Culhuacan, Mexico City, Mexico"],"affiliations":[{"raw_affiliation_string":"Instituto Politecnico Nacional, ESIME Culhuacan, Mexico City, Mexico","institution_ids":["https://openalex.org/I59361560"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054600485","display_name":"\u202aKeiji Yanai\u202c","orcid":"https://orcid.org/0000-0002-0431-183X"},"institutions":[{"id":"https://openalex.org/I20529979","display_name":"University of Electro-Communications","ror":"https://ror.org/02x73b849","country_code":"JP","type":"education","lineage":["https://openalex.org/I20529979"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Keiji Yanai","raw_affiliation_strings":["The University of Electro-Communications, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"The University of Electro-Communications, Tokyo, Japan","institution_ids":["https://openalex.org/I20529979"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5056502006"],"corresponding_institution_ids":["https://openalex.org/I59361560"],"apc_list":null,"apc_paid":null,"fwci":1.5371,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.84746732,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2264","last_page":"2271"},"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":0.9988999962806702,"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":0.9980999827384949,"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":0.8885506391525269},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7755165100097656},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6897724866867065},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6549229621887207},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6146657466888428},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.498476505279541},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.42052268981933594},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4173828065395355},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4169633388519287},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.410474956035614},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.40707072615623474},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37601497769355774}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8885506391525269},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7755165100097656},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6897724866867065},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6549229621887207},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6146657466888428},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.498476505279541},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.42052268981933594},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4173828065395355},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4169633388519287},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.410474956035614},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40707072615623474},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37601497769355774},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/icpr48806.2021.9413176","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9413176","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.6600000262260437,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2340017589","https://openalex.org/W2340897893","https://openalex.org/W2531409750","https://openalex.org/W2560023338","https://openalex.org/W2612445135","https://openalex.org/W2762439315","https://openalex.org/W2803097213","https://openalex.org/W2804860796","https://openalex.org/W2884370868","https://openalex.org/W2886934227","https://openalex.org/W2915478146","https://openalex.org/W2921495890","https://openalex.org/W2921526792","https://openalex.org/W2921781974","https://openalex.org/W2928560789","https://openalex.org/W2947095094","https://openalex.org/W2961666066","https://openalex.org/W2962772649","https://openalex.org/W2963163009","https://openalex.org/W2963419596","https://openalex.org/W2963446712","https://openalex.org/W2963800917","https://openalex.org/W2963840672","https://openalex.org/W2963890956","https://openalex.org/W2964217532","https://openalex.org/W2964259004","https://openalex.org/W2964264300","https://openalex.org/W2964309882","https://openalex.org/W2965380104","https://openalex.org/W2971198903","https://openalex.org/W2981689412","https://openalex.org/W2982083293","https://openalex.org/W2985269212","https://openalex.org/W2987175876","https://openalex.org/W2991471181","https://openalex.org/W2993235622","https://openalex.org/W2994671176","https://openalex.org/W2996621846","https://openalex.org/W2997806675","https://openalex.org/W3023158620","https://openalex.org/W3109301572","https://openalex.org/W4297775537","https://openalex.org/W4299603580","https://openalex.org/W6639824700","https://openalex.org/W6696085341","https://openalex.org/W6703733040","https://openalex.org/W6737324727","https://openalex.org/W6749781174","https://openalex.org/W6751146195","https://openalex.org/W6754123467","https://openalex.org/W6756887525","https://openalex.org/W6757256307","https://openalex.org/W6759144272","https://openalex.org/W6766273390","https://openalex.org/W6768371451","https://openalex.org/W6771640722"],"related_works":["https://openalex.org/W2181948922","https://openalex.org/W2384362569","https://openalex.org/W2055243143","https://openalex.org/W4205302943","https://openalex.org/W1950940422","https://openalex.org/W2129146436","https://openalex.org/W4283822356","https://openalex.org/W2032507829","https://openalex.org/W2060210989","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Recent":[0],"works":[1],"have":[2],"shown":[3],"promising":[4],"results":[5],"applied":[6],"to":[7,39,54,68,98],"real-time":[8,74,83],"semantic":[9,56,75],"segmentation":[10,57,76,86],"tasks.":[11],"To":[12],"maintain":[13,40],"fast":[14,42],"inference":[15,43],"speed,":[16],"most":[17],"of":[18,24,107,111,143,169,192,199],"the":[19,79,101,105,108,112,144,154,173],"existing":[20],"networks":[21],"make":[22],"use":[23,32],"light":[25,190],"decoders,":[26],"or":[27],"they":[28],"simply":[29],"do":[30],"not":[31],"them":[33],"at":[34,177,201,226],"all.":[35],"This":[36],"strategy":[37],"helps":[38],"a":[41,70,189,207],"speed;":[44],"however,":[45],"their":[46],"accuracy":[47,80,171],"performance":[48],"is":[49,96],"significantly":[50],"lower":[51],"in":[52],"comparison":[53],"non-real-time":[55,85],"networks.":[58,87],"In":[59],"this":[60],"paper,":[61],"we":[62,195],"introduce":[63],"two":[64],"key":[65],"modules":[66,147],"aimed":[67],"design":[69],"high-performance":[71],"decoder":[72],"for":[73,77],"reducing":[78],"gap":[81],"between":[82],"and":[84,127,130,140,221],"Our":[88,118,161],"first":[89],"module,":[90,120,125],"Dilated":[91,122],"Asymmetric":[92,123],"Pyramidal":[93],"Fusion":[94],"(DAPF),":[95],"designed":[97],"substantially":[99],"increase":[100],"receptive":[102],"field":[103],"on":[104,172,180,206],"top":[106],"last":[109],"stage":[110],"encoder,":[113],"obtaining":[114],"richer":[115],"contextual":[116,131,149],"features.":[117],"second":[119],"Multi-resolution":[121],"(MDA)":[124],"fuses":[126],"refines":[128],"detail":[129],"information":[132,150],"from":[133,138],"multi-scale":[134],"feature":[135],"maps":[136],"coming":[137],"early":[139],"deeper":[141],"stages":[142],"network.":[145],"Both":[146],"exploit":[148],"without":[151],"excessively":[152],"increasing":[153],"computational":[155],"complexity":[156],"by":[157],"using":[158],"asymmetric":[159],"convolutions.":[160],"proposed":[162],"network":[163],"entitled":[164],"\u201cFASSD-Net\u201d":[165],"reaches":[166],"78.8":[167],"%":[168,198],"mIoU":[170,200],"Cityscapes":[174],"validation":[175],"dataset":[176],"41.1":[178],"FPS":[179,203],"full":[181],"resolution":[182],"images":[183],"(1024":[184],"x":[185],"2048).":[186],"Besides,":[187],"with":[188,213],"version":[191],"our":[193],"network,":[194],"reach":[196],"74.1":[197],"133.1":[202],"(full":[204],"resolution)":[205],"single":[208],"NVIDIA":[209],"GTX":[210],"1080Ti":[211],"card":[212],"no":[214],"additional":[215],"acceleration":[216],"techniques.":[217],"The":[218],"source":[219],"code":[220],"pre-trained":[222],"models":[223],"are":[224],"available":[225],"github.com/GibranBenitez/FASSD-":[227],"Net.":[228]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
