{"id":"https://openalex.org/W4386824854","doi":"https://doi.org/10.1109/tits.2023.3313982","title":"SegTransConv: Transformer and CNN Hybrid Method for Real-Time Semantic Segmentation of Autonomous Vehicles","display_name":"SegTransConv: Transformer and CNN Hybrid Method for Real-Time Semantic Segmentation of Autonomous Vehicles","publication_year":2023,"publication_date":"2023-09-18","ids":{"openalex":"https://openalex.org/W4386824854","doi":"https://doi.org/10.1109/tits.2023.3313982"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2023.3313982","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2023.3313982","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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101658712","display_name":"Jiaqi Fan","orcid":"https://orcid.org/0000-0002-2642-2485"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaqi Fan","raw_affiliation_strings":["Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-2642-2485","affiliations":[{"raw_affiliation_string":"Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064212745","display_name":"Bingzhao Gao","orcid":"https://orcid.org/0000-0001-5155-7835"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bingzhao Gao","raw_affiliation_strings":["School of Automotive Studies, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-5155-7835","affiliations":[{"raw_affiliation_string":"School of Automotive Studies, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053095481","display_name":"Quanbo Ge","orcid":"https://orcid.org/0000-0002-0044-6059"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quanbo Ge","raw_affiliation_strings":["School of Automation, Nanjing University of Information Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-0044-6059","affiliations":[{"raw_affiliation_string":"School of Automation, Nanjing University of Information Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114083242","display_name":"Yabing Ran","orcid":null},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yabing Ran","raw_affiliation_strings":["School of Automotive Studies, Tongji University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automotive Studies, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100360715","display_name":"Jia Zhang","orcid":"https://orcid.org/0009-0006-7482-2885"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jia Zhang","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063286550","display_name":"Hongqing Chu","orcid":"https://orcid.org/0000-0002-8015-9788"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongqing Chu","raw_affiliation_strings":["School of Automotive Studies, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-8015-9788","affiliations":[{"raw_affiliation_string":"School of Automotive Studies, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.2402,"has_fulltext":false,"cited_by_count":54,"citation_normalized_percentile":{"value":0.97087039,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"25","issue":"2","first_page":"1586","last_page":"1601"},"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9951000213623047,"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":0.695832371711731},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6522330045700073},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6145957112312317},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5910678505897522},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5748509764671326},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5035027861595154},{"id":"https://openalex.org/keywords/flops","display_name":"FLOPS","score":0.49298426508903503},{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.48333069682121277},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45303165912628174},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4495314061641693},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4103471040725708},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3618885278701782},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13986128568649292},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09901291131973267},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.08381283283233643}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.695832371711731},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6522330045700073},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6145957112312317},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5910678505897522},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5748509764671326},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5035027861595154},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.49298426508903503},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.48333069682121277},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45303165912628174},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4495314061641693},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4103471040725708},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3618885278701782},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13986128568649292},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09901291131973267},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.08381283283233643},{"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/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2023.3313982","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2023.3313982","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"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.6899999976158142,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G1163267705","display_name":null,"funder_award_id":"62273256","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":82,"referenced_works":["https://openalex.org/W1821462560","https://openalex.org/W1903029394","https://openalex.org/W1913356549","https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2340897893","https://openalex.org/W2531409750","https://openalex.org/W2560023338","https://openalex.org/W2565639579","https://openalex.org/W2630837129","https://openalex.org/W2762439315","https://openalex.org/W2787091153","https://openalex.org/W2884822772","https://openalex.org/W2886934227","https://openalex.org/W2963125010","https://openalex.org/W2963419596","https://openalex.org/W2963890956","https://openalex.org/W2964217532","https://openalex.org/W2971198903","https://openalex.org/W3007072719","https://openalex.org/W3012528238","https://openalex.org/W3027763298","https://openalex.org/W3034806364","https://openalex.org/W3082097505","https://openalex.org/W3131182250","https://openalex.org/W3131500599","https://openalex.org/W3137278571","https://openalex.org/W3138516171","https://openalex.org/W3157525179","https://openalex.org/W3159637683","https://openalex.org/W3159837173","https://openalex.org/W3160694286","https://openalex.org/W3161825146","https://openalex.org/W3169865585","https://openalex.org/W3172265425","https://openalex.org/W3174851543","https://openalex.org/W3175515048","https://openalex.org/W3181515393","https://openalex.org/W3187001198","https://openalex.org/W3190437803","https://openalex.org/W3190492058","https://openalex.org/W3194816901","https://openalex.org/W3201726317","https://openalex.org/W3202424564","https://openalex.org/W3202923600","https://openalex.org/W3211490618","https://openalex.org/W3212622989","https://openalex.org/W3215565096","https://openalex.org/W4212821600","https://openalex.org/W4214493665","https://openalex.org/W4214588794","https://openalex.org/W4214709605","https://openalex.org/W4214893857","https://openalex.org/W4221154336","https://openalex.org/W4221166185","https://openalex.org/W4285144577","https://openalex.org/W4293406525","https://openalex.org/W4297775537","https://openalex.org/W4306311936","https://openalex.org/W4306804783","https://openalex.org/W4309660743","https://openalex.org/W4309819116","https://openalex.org/W4312785900","https://openalex.org/W4312815172","https://openalex.org/W4312950730","https://openalex.org/W4312981390","https://openalex.org/W4313151123","https://openalex.org/W4318719552","https://openalex.org/W4386065698","https://openalex.org/W6631190155","https://openalex.org/W6717372056","https://openalex.org/W6737664043","https://openalex.org/W6739696289","https://openalex.org/W6739901393","https://openalex.org/W6751146195","https://openalex.org/W6760613829","https://openalex.org/W6788135285","https://openalex.org/W6797399245","https://openalex.org/W6803677459","https://openalex.org/W6810565932","https://openalex.org/W6846053352","https://openalex.org/W6848963243"],"related_works":["https://openalex.org/W2062399876","https://openalex.org/W2607795551","https://openalex.org/W4315697128","https://openalex.org/W3155117723","https://openalex.org/W1991429770","https://openalex.org/W1983892167","https://openalex.org/W2281134365","https://openalex.org/W4310746709","https://openalex.org/W4385574037","https://openalex.org/W4212888438"],"abstract_inverted_index":{"Real-time":[0],"and":[1,22,26,42,55,73,131,143,154,158],"high-performance":[2],"semantic":[3],"segmentation":[4,135],"is":[5,49,100,120],"a":[6,24,38,116],"crucial":[7],"task":[8],"in":[9,46,58],"the":[10,43,63,67,71,75,79,82,88,96,104,108,111,125,148,163],"scene":[11],"understanding":[12],"of":[13,51,70,110,133,150,166],"autonomous":[14],"vehicles.":[15],"This":[16],"paper":[17],"focuses":[18],"on":[19,139],"this":[20,61],"issue":[21],"proposes":[23],"transformer":[25,53],"convolutional":[27],"neural":[28],"networks":[29],"(CNN)":[30],"hybrid":[31],"encoder-decoder":[32],"structure":[33],"SegTransConv.":[34],"Firstly,":[35],"we":[36],"present":[37],"four-stage":[39],"hierarchical":[40],"encoder,":[41],"feature":[44,83,90],"extractor":[45],"each":[47],"stage":[48],"composed":[50],"two":[52,140],"layers":[54],"CNN":[56],"modules":[57],"series.":[59],"In":[60,78],"way,":[62],"encoder":[64],"better":[65],"exploits":[66],"global":[68],"contexts":[69],"input":[72,171],"expands":[74],"receptive":[76],"fields.":[77],"U-shape":[80],"decoder,":[81],"maps":[84],"are":[85],"upsampled":[86],"through":[87],"proposed":[89],"enhancement":[91],"upsampling":[92],"module":[93],"(FE_Up).":[94],"Then":[95],"knowledge":[97],"distillation":[98],"strategy":[99],"leveraged":[101],"to":[102,122],"improve":[103],"model":[105],"performance":[106],"under":[107],"guidance":[109],"teacher":[112],"network":[113],"STDCNet.":[114],"Finally,":[115],"novel":[117],"evaluation":[118],"metric":[119],"designed":[121],"comprehensively":[123],"assess":[124],"accuracy,":[126],"speed,":[127],"floating-point":[128],"operations":[129],"(FLOPs),":[130],"parameters":[132],"real-time":[134],"methods.":[136],"Extensive":[137],"experiments":[138],"public":[141],"datasets":[142],"self-collected":[144],"images":[145],"have":[146],"evaluated":[147],"effectiveness":[149],"our":[151],"method.":[152],"SegTransConv-A":[153],"SegTransConv-B":[155],"obtain":[156],"72.8%":[157],"73.0%":[159],"mIoU,":[160],"respectively,":[161],"at":[162],"inference":[164],"speed":[165],"68.0":[167],"FPS":[168],"with":[169],"an":[170],"resolution":[172],"of$1024\\times":[173],"512$.":[174]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":30},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}