{"id":"https://openalex.org/W3010074503","doi":"https://doi.org/10.1109/wacv45572.2020.9093264","title":"Multi Receptive Field Network for Semantic Segmentation","display_name":"Multi Receptive Field Network for Semantic Segmentation","publication_year":2020,"publication_date":"2020-03-01","ids":{"openalex":"https://openalex.org/W3010074503","doi":"https://doi.org/10.1109/wacv45572.2020.9093264","mag":"3010074503"},"language":"en","primary_location":{"id":"doi:10.1109/wacv45572.2020.9093264","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093264","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","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/A5101561037","display_name":"Jianlong Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210155230","display_name":"Samsung (China)","ror":"https://ror.org/04yt00889","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210155230"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianlong Yuan","raw_affiliation_strings":["Samsung Research China Beijing"],"affiliations":[{"raw_affiliation_string":"Samsung Research China Beijing","institution_ids":["https://openalex.org/I4210155230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101086047","display_name":"Zelu Deng","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zelu Deng","raw_affiliation_strings":["University of Electronic Science and Technology of China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022041233","display_name":"Shu Wang","orcid":"https://orcid.org/0009-0005-4006-3828"},"institutions":[{"id":"https://openalex.org/I4210155230","display_name":"Samsung (China)","ror":"https://ror.org/04yt00889","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210155230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shu Wang","raw_affiliation_strings":["Samsung Research China Beijing"],"affiliations":[{"raw_affiliation_string":"Samsung Research China Beijing","institution_ids":["https://openalex.org/I4210155230"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102328739","display_name":"Zhenbo Luo","orcid":null},"institutions":[{"id":"https://openalex.org/I4210155230","display_name":"Samsung (China)","ror":"https://ror.org/04yt00889","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210155230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenbo Luo","raw_affiliation_strings":["Samsung Research China Beijing"],"affiliations":[{"raw_affiliation_string":"Samsung Research China Beijing","institution_ids":["https://openalex.org/I4210155230"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101561037"],"corresponding_institution_ids":["https://openalex.org/I4210155230"],"apc_list":null,"apc_paid":null,"fwci":1.6679,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.86220675,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"2020","issue":null,"first_page":"1883","last_page":"1892"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9990000128746033,"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":0.8379133939743042},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7462798357009888},{"id":"https://openalex.org/keywords/pascal","display_name":"Pascal (unit)","score":0.6880151629447937},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6711117625236511},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5666143894195557},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5633678436279297},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5471873879432678},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5112135410308838},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4547833502292633},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.44241583347320557},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4111535847187042},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3895982503890991},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06584879755973816},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.054976195096969604}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8379133939743042},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7462798357009888},{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.6880151629447937},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6711117625236511},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5666143894195557},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5633678436279297},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5471873879432678},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5112135410308838},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4547833502292633},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.44241583347320557},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4111535847187042},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3895982503890991},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06584879755973816},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.054976195096969604},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/wacv45572.2020.9093264","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093264","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},{"id":"mag:3163732906","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002218577607042","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","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":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8500000238418579,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W1569892065","https://openalex.org/W1861492603","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1910657905","https://openalex.org/W2031489346","https://openalex.org/W2054279472","https://openalex.org/W2084134149","https://openalex.org/W2095844239","https://openalex.org/W2116877738","https://openalex.org/W2137881638","https://openalex.org/W2144794286","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2340897893","https://openalex.org/W2412782625","https://openalex.org/W2531409750","https://openalex.org/W2535516436","https://openalex.org/W2536208356","https://openalex.org/W2560023338","https://openalex.org/W2563705555","https://openalex.org/W2592939477","https://openalex.org/W2630837129","https://openalex.org/W2745943519","https://openalex.org/W2772805599","https://openalex.org/W2799166040","https://openalex.org/W2799213142","https://openalex.org/W2890498246","https://openalex.org/W2890862129","https://openalex.org/W2891778567","https://openalex.org/W2895420332","https://openalex.org/W2950053619","https://openalex.org/W2952147788","https://openalex.org/W2956887593","https://openalex.org/W2963073398","https://openalex.org/W2963136578","https://openalex.org/W2963446712","https://openalex.org/W2963516811","https://openalex.org/W2963563573","https://openalex.org/W2963727650","https://openalex.org/W2963728677","https://openalex.org/W2963815618","https://openalex.org/W2963840672","https://openalex.org/W2963881378","https://openalex.org/W2964309882","https://openalex.org/W2964350391","https://openalex.org/W2966926453","https://openalex.org/W3017143921","https://openalex.org/W3099155473","https://openalex.org/W4299298190","https://openalex.org/W6639102338","https://openalex.org/W6639780620","https://openalex.org/W6639824700","https://openalex.org/W6674793120","https://openalex.org/W6680357304","https://openalex.org/W6684191040","https://openalex.org/W6696085341","https://openalex.org/W6704278359","https://openalex.org/W6715287400","https://openalex.org/W6730587030","https://openalex.org/W6739696289","https://openalex.org/W6743122958","https://openalex.org/W6748481559","https://openalex.org/W6754899465","https://openalex.org/W6754942058"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2745001401","https://openalex.org/W4321353415","https://openalex.org/W1663079876","https://openalex.org/W2130974462","https://openalex.org/W972276598","https://openalex.org/W2069133146","https://openalex.org/W4246352526","https://openalex.org/W2493838176","https://openalex.org/W4297686120"],"abstract_inverted_index":{"Semantic":[0],"segmentation":[1,139],"is":[2,12,114],"one":[3],"of":[4,40,71,82,120,148],"the":[5,57,63,69,79,87,105,118,151,159],"key":[6],"tasks":[7],"in":[8,21,44,116],"computer":[9],"vision,":[10],"which":[11,113],"to":[13,18,66,75,78],"assign":[14],"a":[15,92,145],"category":[16],"label":[17],"each":[19],"pixel":[20],"an":[22,45,110],"image.":[23],"Despite":[24],"significant":[25],"progress":[26],"achieved":[27],"recently,":[28],"most":[29],"existing":[30],"methods":[31],"still":[32],"suffer":[33],"from":[34],"two":[35,124,136],"challenging":[36],"issues:":[37],"l)the":[38],"size":[39],"objects":[41],"and":[42,154],"stuff":[43],"image":[46],"can":[47],"be":[48],"very":[49],"diverse,":[50],"demanding":[51],"for":[52],"incorporating":[53],"multi-scale":[54,100],"features":[55,101],"into":[56,102],"fully":[58],"convolutional":[59,83],"networks":[60],"(FCNs);":[61],"2)":[62],"pixels":[64],"close":[65],"or":[67],"at":[68],"boundaries":[70,119],"object/stuff":[72],"are":[73],"hard":[74],"classify":[76],"due":[77],"intrinsic":[80],"weakness":[81],"networks.":[84],"To":[85],"address":[86],"first":[88],"issue,":[89,107],"we":[90,108,143],"propose":[91],"new":[93,132],"Multi-Receptive":[94],"Field":[95,129],"Module":[96],"(MRFM),":[97],"explicitly":[98],"taking":[99],"account.":[103],"For":[104],"second":[106],"design":[109],"edge-aware":[111],"loss":[112],"effective":[115],"distinguishing":[117],"object/stuff.":[121],"With":[122],"these":[123],"designs,":[125],"our":[126],"Multi":[127],"Receptive":[128],"Network":[130],"achieves":[131],"state-of-the-art":[133],"results":[134],"on":[135,150,158],"widely-used":[137],"semantic":[138],"benchmark":[140],"datasets.":[141],"Specifically,":[142],"achieve":[144],"mean":[146,156],"IoU":[147,157],"83.0%":[149],"Cityscapes":[152],"dataset":[153],"88.4%":[155],"Pascal":[160],"VOC2012":[161],"dataset.":[162]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":5}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
