{"id":"https://openalex.org/W4206210197","doi":"https://doi.org/10.1109/tits.2021.3139001","title":"Efficient Semantic Segmentation via Self-Attention and Self-Distillation","display_name":"Efficient Semantic Segmentation via Self-Attention and Self-Distillation","publication_year":2022,"publication_date":"2022-01-11","ids":{"openalex":"https://openalex.org/W4206210197","doi":"https://doi.org/10.1109/tits.2021.3139001"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2021.3139001","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2021.3139001","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://discovery.ucl.ac.uk/10141780/1/ShuminAn-T-ITS-accepted.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046787619","display_name":"Shumin An","orcid":"https://orcid.org/0000-0002-0419-9278"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"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":true,"raw_author_name":"Shumin An","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China","Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009239895","display_name":"Qingmin Liao","orcid":"https://orcid.org/0000-0002-7509-3964"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"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":"Qingmin Liao","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China","Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089642905","display_name":"Zongqing Lu","orcid":"https://orcid.org/0000-0003-3967-2704"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"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":"Zongqing Lu","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China","Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079361172","display_name":"Jing\u2010Hao Xue","orcid":"https://orcid.org/0000-0003-1174-610X"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jing-Hao Xue","raw_affiliation_strings":["Department of Statistical Science, University College London, London, U.K"],"affiliations":[{"raw_affiliation_string":"Department of Statistical Science, University College London, London, U.K","institution_ids":["https://openalex.org/I45129253"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5046787619"],"corresponding_institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":6.0243,"has_fulltext":true,"cited_by_count":60,"citation_normalized_percentile":{"value":0.97370393,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"23","issue":"9","first_page":"15256","last_page":"15266"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9969000220298767,"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":0.9965000152587891,"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":0.740875244140625},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7372165322303772},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.7075645327568054},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6296476125717163},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5556765794754028},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5080740451812744},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.4553632140159607},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3929636478424072},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.11389392614364624},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.0851699709892273},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.06887921690940857}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.740875244140625},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7372165322303772},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.7075645327568054},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6296476125717163},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5556765794754028},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5080740451812744},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.4553632140159607},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3929636478424072},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.11389392614364624},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0851699709892273},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.06887921690940857},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tits.2021.3139001","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2021.3139001","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"},{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:10141780","is_oa":true,"landing_page_url":"https://discovery.ucl.ac.uk/id/eprint/10141780/","pdf_url":"https://discovery.ucl.ac.uk/10141780/1/ShuminAn-T-ITS-accepted.pdf","source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"   IEEE Transactions on Intelligent Transportation Systems       (2022)     (In press).  ","raw_type":"Article"}],"best_oa_location":{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:10141780","is_oa":true,"landing_page_url":"https://discovery.ucl.ac.uk/id/eprint/10141780/","pdf_url":"https://discovery.ucl.ac.uk/10141780/1/ShuminAn-T-ITS-accepted.pdf","source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"   IEEE Transactions on Intelligent Transportation Systems       (2022)     (In press).  ","raw_type":"Article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5529815295","display_name":null,"funder_award_id":"61771276","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5949066147","display_name":null,"funder_award_id":"JCYJ20170817161056260","funder_id":"https://openalex.org/F4320335972","funder_display_name":"Special Foundation for the Development of Strategic Emerging Industries of Shenzhen"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335972","display_name":"Special Foundation for the Development of Strategic Emerging Industries of Shenzhen","ror":null}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4206210197.pdf"},"referenced_works_count":57,"referenced_works":["https://openalex.org/W1821462560","https://openalex.org/W1913356549","https://openalex.org/W1923697677","https://openalex.org/W2019329118","https://openalex.org/W2124592697","https://openalex.org/W2194775991","https://openalex.org/W2204696980","https://openalex.org/W2340897893","https://openalex.org/W2395611524","https://openalex.org/W2412782625","https://openalex.org/W2560023338","https://openalex.org/W2737258237","https://openalex.org/W2750432752","https://openalex.org/W2778955544","https://openalex.org/W2799213142","https://openalex.org/W2883780447","https://openalex.org/W2890782586","https://openalex.org/W2894332907","https://openalex.org/W2952787292","https://openalex.org/W2954054736","https://openalex.org/W2955058313","https://openalex.org/W2963091558","https://openalex.org/W2963163009","https://openalex.org/W2963166928","https://openalex.org/W2963418739","https://openalex.org/W2963727650","https://openalex.org/W2963840672","https://openalex.org/W2963881378","https://openalex.org/W2971198903","https://openalex.org/W2981441441","https://openalex.org/W2981689412","https://openalex.org/W2987861506","https://openalex.org/W2990138076","https://openalex.org/W2997006708","https://openalex.org/W2997941347","https://openalex.org/W3034958977","https://openalex.org/W3049435445","https://openalex.org/W3143801622","https://openalex.org/W3186802005","https://openalex.org/W4293406525","https://openalex.org/W4297775537","https://openalex.org/W6640295612","https://openalex.org/W6696085341","https://openalex.org/W6717372056","https://openalex.org/W6737664043","https://openalex.org/W6752378368","https://openalex.org/W6754879843","https://openalex.org/W6755536945","https://openalex.org/W6769955919","https://openalex.org/W6770515439","https://openalex.org/W6772311520","https://openalex.org/W6772695483","https://openalex.org/W6773815586","https://openalex.org/W6782512527","https://openalex.org/W6790307280","https://openalex.org/W6792358924","https://openalex.org/W6842607031"],"related_works":["https://openalex.org/W3026162553","https://openalex.org/W1603736412","https://openalex.org/W2344382886","https://openalex.org/W4304185162","https://openalex.org/W19111321","https://openalex.org/W4379231730","https://openalex.org/W2412887479","https://openalex.org/W2061685118","https://openalex.org/W32245304","https://openalex.org/W2890372105"],"abstract_inverted_index":{"Lightweight":[0],"models":[1],"are":[2],"pivotal":[3],"in":[4],"efficient":[5,34],"semantic":[6,35,91],"segmentation,":[7],"but":[8],"they":[9],"often":[10],"suffer":[11],"from":[12,61,80],"insufficient":[13],"context":[14,45,58,73,79],"information":[15,46],"due":[16],"to":[17,33,47,65,83],"limited":[18],"convolution":[19],"and":[20,69,103],"small":[21,48,66],"receptive":[22],"field.":[23],"To":[24],"address":[25],"this":[26],"problem,":[27],"we":[28],"propose":[29],"a":[30,51,71],"tailored":[31],"approach":[32],"segmentation":[36],"by":[37],"leveraging":[38],"two":[39],"complementary":[40],"distillation":[41,53,74],"schemes":[42],"for":[43,89],"supplementing":[44],"networks:":[49],"1)":[50],"self-attention":[52],"scheme,":[54,75],"which":[55,76],"transfers":[56,77],"long-range":[57],"knowledge":[59],"adaptively":[60],"large":[62],"teacher":[63],"networks":[64,88],"student":[67,87],"networks;":[68],"2)":[70],"layer-wise":[72],"structured":[78],"deep":[81],"layers":[82,85],"shallow":[84,95],"within":[86],"promoting":[90],"consistency":[92],"of":[93,110],"the":[94,100,108],"layers.":[96],"Extensive":[97],"experiments":[98],"on":[99],"ADE20K,":[101],"Cityscapes,":[102],"Camvid":[104],"datasets":[105],"well":[106],"demonstrate":[107],"effectiveness":[109],"our":[111],"proposal.":[112]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":23},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":5}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
