{"id":"https://openalex.org/W4383108765","doi":"https://doi.org/10.1109/icra48891.2023.10161200","title":"TransRSS: Transformer-based Radar Semantic Segmentation","display_name":"TransRSS: Transformer-based Radar Semantic Segmentation","publication_year":2023,"publication_date":"2023-05-29","ids":{"openalex":"https://openalex.org/W4383108765","doi":"https://doi.org/10.1109/icra48891.2023.10161200"},"language":"en","primary_location":{"id":"doi:10.1109/icra48891.2023.10161200","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48891.2023.10161200","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Robotics and Automation (ICRA)","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/A5111213629","display_name":"Hao Zou","orcid":null},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hao Zou","raw_affiliation_strings":["Alibaba Group,Hangzhou,China","Alibaba Group, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group,Hangzhou,China","institution_ids":["https://openalex.org/I45928872"]},{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014216586","display_name":"Zhen Xie","orcid":"https://orcid.org/0000-0001-8798-9592"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Xie","raw_affiliation_strings":["Alibaba Group,Hangzhou,China","Alibaba Group, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group,Hangzhou,China","institution_ids":["https://openalex.org/I45928872"]},{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087564348","display_name":"Jiarong Ou","orcid":null},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiarong Ou","raw_affiliation_strings":["Alibaba Group,Hangzhou,China","Alibaba Group, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group,Hangzhou,China","institution_ids":["https://openalex.org/I45928872"]},{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085567159","display_name":"Yutao Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yutao Gao","raw_affiliation_strings":["Alibaba Group,Hangzhou,China","Alibaba Group, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group,Hangzhou,China","institution_ids":["https://openalex.org/I45928872"]},{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5111213629"],"corresponding_institution_ids":["https://openalex.org/I45928872"],"apc_list":null,"apc_paid":null,"fwci":1.5444,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.81008283,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"6965","last_page":"6972"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11609","display_name":"Geophysical Methods and Applications","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11609","display_name":"Geophysical Methods and Applications","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T11698","display_name":"Underwater Acoustics Research","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7997401356697083},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.690569281578064},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6761664748191833},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6089776754379272},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5992847681045532},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.5722083449363708},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5003054141998291},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4757658839225769},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.47446542978286743},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.47261667251586914},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4524189829826355},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.405484139919281},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11766722798347473},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07618770003318787}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7997401356697083},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.690569281578064},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6761664748191833},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6089776754379272},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5992847681045532},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.5722083449363708},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5003054141998291},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4757658839225769},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.47446542978286743},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.47261667251586914},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4524189829826355},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.405484139919281},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11766722798347473},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07618770003318787},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra48891.2023.10161200","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48891.2023.10161200","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":70,"referenced_works":["https://openalex.org/W595851582","https://openalex.org/W1522301498","https://openalex.org/W1836465849","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2194775991","https://openalex.org/W2560609797","https://openalex.org/W2741069557","https://openalex.org/W2798965597","https://openalex.org/W2891649842","https://openalex.org/W2896457183","https://openalex.org/W2939308603","https://openalex.org/W2962914239","https://openalex.org/W2963121255","https://openalex.org/W2963351448","https://openalex.org/W2963844898","https://openalex.org/W2964110616","https://openalex.org/W2964309882","https://openalex.org/W2990710319","https://openalex.org/W2994788716","https://openalex.org/W2995549977","https://openalex.org/W2996476754","https://openalex.org/W3035481945","https://openalex.org/W3035574168","https://openalex.org/W3036394006","https://openalex.org/W3086796143","https://openalex.org/W3094502228","https://openalex.org/W3094632837","https://openalex.org/W3097947358","https://openalex.org/W3103612787","https://openalex.org/W3105073457","https://openalex.org/W3118132944","https://openalex.org/W3118479569","https://openalex.org/W3120351402","https://openalex.org/W3120815051","https://openalex.org/W3135437426","https://openalex.org/W3137763535","https://openalex.org/W3138516171","https://openalex.org/W3161421216","https://openalex.org/W3166470370","https://openalex.org/W3167214600","https://openalex.org/W3170874841","https://openalex.org/W3176740453","https://openalex.org/W3180629550","https://openalex.org/W3197392487","https://openalex.org/W3208941688","https://openalex.org/W3209826827","https://openalex.org/W4214736753","https://openalex.org/W4214755140","https://openalex.org/W4285071849","https://openalex.org/W4302152706","https://openalex.org/W4312492443","https://openalex.org/W4312811864","https://openalex.org/W4312931360","https://openalex.org/W4385245566","https://openalex.org/W6631190155","https://openalex.org/W6638667902","https://openalex.org/W6639824700","https://openalex.org/W6739778489","https://openalex.org/W6739901393","https://openalex.org/W6748481559","https://openalex.org/W6755207826","https://openalex.org/W6763422710","https://openalex.org/W6771471907","https://openalex.org/W6782812182","https://openalex.org/W6784333009","https://openalex.org/W6788135285","https://openalex.org/W6791291431","https://openalex.org/W6792269122","https://openalex.org/W6845813885"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W2110523656","https://openalex.org/W1482209366","https://openalex.org/W2053819089"],"abstract_inverted_index":{"Radar":[0,40],"semantic":[1,63,84],"segmentation":[2,64,171],"is":[3,15],"a":[4,35,130],"challenging":[5],"task":[6],"in":[7],"environmental":[8],"understanding,":[9],"due":[10],"as":[11],"the":[12,59,68,71,87,94,105,110,117,124,141,156,167],"radar":[13,53,62,170],"data":[14],"noisy":[16],"and":[17,37,48,65,76,82,159],"suffers":[18],"measurement":[19],"ambiguities,":[20],"which":[21,144],"could":[22],"lead":[23],"to":[24,46,78,100,104,119,135],"poor":[25],"feature":[26,50,151],"learning.":[27],"To":[28],"better":[29],"tackle":[30],"such":[31],"difficulties,":[32],"we":[33,128],"present":[34],"novel":[36],"high-performance":[38],"Transformer-based":[39],"Semantic":[41],"Segmentation":[42],"method,":[43],"named":[44],"TransRSS,":[45],"effectively":[47],"efficiently":[49],"extraction":[51],"for":[52,149],"segmentation.":[54],"Our":[55],"approach":[56],"first":[57],"introduces":[58],"transformer":[60,77,118],"into":[61],"deeply":[66],"integrates":[67],"merits":[69],"of":[70,93,116],"Convolutional":[72],"Neural":[73],"Network":[74],"(CNN)":[75],"extract":[79],"more":[80],"discriminative":[81],"global-level":[83],"features.":[85],"On":[86,109],"one":[88],"hand,":[89,112],"it":[90,113],"takes":[91,114],"advantage":[92,115],"CNN":[95],"with":[96,123,173],"flexible":[97],"receptive":[98],"fields":[99],"process":[101],"images":[102],"thanks":[103],"shift":[106],"convolution":[107],"scheme.":[108],"other":[111],"model":[120],"long-range":[121],"dependency":[122],"self-attention":[125],"mechanism.":[126],"Meanwhile,":[127],"propose":[129],"Dual":[131],"Position":[132],"Attention":[133],"module":[134],"aggregate":[136],"rich":[137],"context":[138],"interdependencies":[139],"between":[140],"multi-view":[142],"features,":[143],"achieves":[145],"an":[146],"implicit":[147],"mechanism":[148],"adaptively":[150],"aggregation.":[152],"Extensive":[153],"experiments":[154],"on":[155],"CARRADA":[157],"dataset":[158,161],"RADIal":[160],"demonstrate":[162],"that":[163],"our":[164],"TransRSS":[165],"surpasses":[166],"state-of-the-art":[168],"(SOTA)":[169],"methods":[172],"remarkable":[174],"margins.":[175]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-23T09:07:50.710637","created_date":"2025-10-10T00:00:00"}