{"id":"https://openalex.org/W3205692110","doi":"https://doi.org/10.1109/icra48506.2021.9561558","title":"Feature Enhanced Projection Network for Zero-shot Semantic Segmentation","display_name":"Feature Enhanced Projection Network for Zero-shot Semantic Segmentation","publication_year":2021,"publication_date":"2021-05-30","ids":{"openalex":"https://openalex.org/W3205692110","doi":"https://doi.org/10.1109/icra48506.2021.9561558","mag":"3205692110"},"language":"en","primary_location":{"id":"doi:10.1109/icra48506.2021.9561558","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48506.2021.9561558","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Robotics and Automation (ICRA)","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/A5113933583","display_name":"Hongchao Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongchao Lu","raw_affiliation_strings":["Department of Computer Science, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102915714","display_name":"Longwei Fang","orcid":"https://orcid.org/0000-0002-2857-9574"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Longwei Fang","raw_affiliation_strings":["Computer Vision Group, Intel, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Vision Group, Intel, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078405581","display_name":"Matthieu Gaetan Lin","orcid":"https://orcid.org/0009-0004-4265-6830"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Matthieu Lin","raw_affiliation_strings":["Department of Computer Science, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102011846","display_name":"Zhidong Deng","orcid":"https://orcid.org/0000-0001-9970-1023"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhidong Deng","raw_affiliation_strings":["Department of Computer Science, State Key Laboratory of Intelligent Technology and Systems, THUAI, BNRist, Center for Intelligent Connected Vehicles and Transportation, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, State Key Laboratory of Intelligent Technology and Systems, THUAI, BNRist, Center for Intelligent Connected Vehicles and Transportation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"14011","last_page":"14017"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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":0.9995999932289124,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.996999979019165,"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":0.7512798309326172},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6846120953559875},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6760038137435913},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6355025768280029},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6254948377609253},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.6023350358009338},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5764937996864319},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5759837627410889},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5107707977294922},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5095451474189758},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5077224969863892},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4850570261478424},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4410329759120941},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.42358121275901794},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1983996033668518},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.07278081774711609},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.06085038185119629}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7512798309326172},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6846120953559875},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6760038137435913},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6355025768280029},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6254948377609253},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.6023350358009338},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5764937996864319},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5759837627410889},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5107707977294922},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5095451474189758},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5077224969863892},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4850570261478424},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4410329759120941},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.42358121275901794},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1983996033668518},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.07278081774711609},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.06085038185119629},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra48506.2021.9561558","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48506.2021.9561558","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.49000000953674316,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320316083","display_name":"Tencent","ror":"https://ror.org/00hhjss72"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1495267108","https://openalex.org/W1903029394","https://openalex.org/W1945608308","https://openalex.org/W2037227137","https://openalex.org/W2109317801","https://openalex.org/W2123024445","https://openalex.org/W2125215748","https://openalex.org/W2144794286","https://openalex.org/W2153579005","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2412782625","https://openalex.org/W2552383788","https://openalex.org/W2552414813","https://openalex.org/W2560023338","https://openalex.org/W2563351168","https://openalex.org/W2585521554","https://openalex.org/W2603705233","https://openalex.org/W2630837129","https://openalex.org/W2793668851","https://openalex.org/W2799074129","https://openalex.org/W2806366596","https://openalex.org/W2924485953","https://openalex.org/W2963032190","https://openalex.org/W2963538198","https://openalex.org/W2963706010","https://openalex.org/W2963881378","https://openalex.org/W2963960318","https://openalex.org/W2964309882","https://openalex.org/W2971113548","https://openalex.org/W2990947836","https://openalex.org/W2994827984","https://openalex.org/W3049293589","https://openalex.org/W3088431063","https://openalex.org/W3106029750","https://openalex.org/W4285651291","https://openalex.org/W4294170691","https://openalex.org/W6678470764","https://openalex.org/W6682691769","https://openalex.org/W6731031554","https://openalex.org/W6739696289","https://openalex.org/W6748481559","https://openalex.org/W6749731209","https://openalex.org/W6763578275","https://openalex.org/W6783607138"],"related_works":["https://openalex.org/W2055243143","https://openalex.org/W2375480909","https://openalex.org/W2353314428","https://openalex.org/W4321636575","https://openalex.org/W2357796999","https://openalex.org/W2045526782","https://openalex.org/W2012019886","https://openalex.org/W2741131631","https://openalex.org/W1986418932","https://openalex.org/W1499137908"],"abstract_inverted_index":{"In":[0,45,67,110],"environmental":[1],"perception":[2],"of":[3,13,60,107,116],"autonomous":[4],"driving,":[5],"zero-shot":[6],"semantic":[7,42,65],"segmentation":[8,76,141],"that":[9,56,146,164],"can":[10],"make":[11],"prediction":[12,137],"new":[14,168],"categories":[15,39,118],"without":[16],"using":[17,100],"any":[18],"labeled":[19],"training":[20],"samples":[21],"is":[22,34,119,132],"considered":[23],"as":[24,79],"a":[25,50,75,129],"challenging":[26],"task.":[27],"One":[28],"key":[29],"step":[30],"in":[31,143],"this":[32,46],"task":[33],"to":[35,63,74,80,98,103,134,172],"transfer":[36],"knowledge":[37,62],"across":[38],"via":[40],"auxiliary":[41],"word":[43],"embeddings.":[44],"paper,":[47],"we":[48],"propose":[49],"feature":[51],"enhanced":[52],"projection":[53,70],"network":[54,77],"(FEPNet)":[55],"takes":[57],"full":[58],"advantage":[59],"transferred":[61,97,125],"enrich":[64],"representations.":[66],"FEPNet,":[68],"two":[69],"layers":[71],"are":[72,96],"added":[73],"so":[78],"map":[81],"features":[82,95,124],"into":[83],"seen":[84,108,148],"(S)":[85],"and":[86,149],"unseen":[87,117,150],"(U)":[88],"category":[89],"spaces,":[90],"respectively.":[91],"During":[92],"training,":[93],"U-space":[94],"S-space":[99],"similarity":[101],"relations":[102],"enhance":[104],"the":[105,111,114],"representation":[106,115],"categories.":[109,151],"inference":[112],"stage,":[113],"also":[120],"strengthened":[121],"by":[122,139],"incorporating":[123],"from":[126],"S-space.":[127],"Moreover,":[128],"novel":[130],"strategy":[131],"proposed":[133],"effectively":[135],"alleviate":[136],"bias":[138],"performing":[140],"independently":[142],"separate":[144],"areas":[145],"contain":[147],"We":[152],"conduct":[153],"extensive":[154],"experiments":[155],"on":[156],"three":[157],"benchmark":[158],"datasets.":[159],"The":[160],"experimental":[161],"results":[162,170],"show":[163],"our":[165],"FEPNet":[166],"achieves":[167],"state-of-the-art":[169],"compared":[171],"existing":[173],"approaches.":[174]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
