{"id":"https://openalex.org/W2886362581","doi":"https://doi.org/10.1007/s41095-018-0116-x","title":"Traffic signal detection and classification in street views using an attention model","display_name":"Traffic signal detection and classification in street views using an attention model","publication_year":2018,"publication_date":"2018-08-03","ids":{"openalex":"https://openalex.org/W2886362581","doi":"https://doi.org/10.1007/s41095-018-0116-x","mag":"2886362581"},"language":"en","primary_location":{"id":"doi:10.1007/s41095-018-0116-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41095-018-0116-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41095-018-0116-x.pdf","source":{"id":"https://openalex.org/S2487656537","display_name":"Computational Visual Media","issn_l":"2096-0433","issn":["2096-0433","2096-0662"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Visual Media","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://link.springer.com/content/pdf/10.1007/s41095-018-0116-x.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039484973","display_name":"Yifan Lu","orcid":"https://orcid.org/0000-0001-6184-6200"},"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":true,"raw_author_name":"Yifan Lu","raw_affiliation_strings":["TNList, Tsinghua University, Beijing 100084, China","TNList, Tsinghua University, Beijing, 100084, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TNList, Tsinghua University, Beijing 100084, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"TNList, Tsinghua University, Beijing, 100084, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101628252","display_name":"Jiaming Lu","orcid":"https://orcid.org/0000-0002-7793-0463"},"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":"Jiaming Lu","raw_affiliation_strings":["TNList, Tsinghua University, Beijing 100084, China","TNList, Tsinghua University, Beijing, 100084, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TNList, Tsinghua University, Beijing 100084, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"TNList, Tsinghua University, Beijing, 100084, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049883689","display_name":"Song\u2013Hai Zhang","orcid":"https://orcid.org/0000-0003-0460-1586"},"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":"Songhai Zhang","raw_affiliation_strings":["TNList, Tsinghua University, Beijing 100084, China","TNList, Tsinghua University, Beijing, 100084, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TNList, Tsinghua University, Beijing 100084, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"TNList, Tsinghua University, Beijing, 100084, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102977753","display_name":"Peter Hall","orcid":"https://orcid.org/0009-0006-5699-5483"},"institutions":[{"id":"https://openalex.org/I51601045","display_name":"University of Bath","ror":"https://ror.org/002h8g185","country_code":"GB","type":"education","lineage":["https://openalex.org/I51601045"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Peter Hall","raw_affiliation_strings":["Department of Computer Science, University of Bath, United Kingdom","Department of Computer Science, University of Bath, Bath, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Bath, United Kingdom","institution_ids":["https://openalex.org/I51601045"]},{"raw_affiliation_string":"Department of Computer Science, University of Bath, Bath, UK","institution_ids":["https://openalex.org/I51601045"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5039484973"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":4.2413,"has_fulltext":true,"cited_by_count":106,"citation_normalized_percentile":{"value":0.95876528,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"4","issue":"3","first_page":"253","last_page":"266"},"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/T11605","display_name":"Visual Attention and Saliency Detection","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"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9954000115394592,"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":0.81815505027771},{"id":"https://openalex.org/keywords/generality","display_name":"Generality","score":0.8088341355323792},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7616673111915588},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6391109228134155},{"id":"https://openalex.org/keywords/traffic-sign-recognition","display_name":"Traffic sign recognition","score":0.634986400604248},{"id":"https://openalex.org/keywords/traffic-sign","display_name":"Traffic sign","score":0.5806903839111328},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5701597929000854},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.55164635181427},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5295938849449158},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5035976767539978},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5008339881896973},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.49785566329956055},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43303412199020386},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38454216718673706},{"id":"https://openalex.org/keywords/sign","display_name":"Sign (mathematics)","score":0.2991369962692261},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07564815878868103}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.81815505027771},{"id":"https://openalex.org/C2780767217","wikidata":"https://www.wikidata.org/wiki/Q5532421","display_name":"Generality","level":2,"score":0.8088341355323792},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7616673111915588},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6391109228134155},{"id":"https://openalex.org/C6528762","wikidata":"https://www.wikidata.org/wiki/Q1574298","display_name":"Traffic sign recognition","level":4,"score":0.634986400604248},{"id":"https://openalex.org/C2983860417","wikidata":"https://www.wikidata.org/wiki/Q170285","display_name":"Traffic sign","level":3,"score":0.5806903839111328},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5701597929000854},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.55164635181427},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5295938849449158},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5035976767539978},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5008339881896973},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.49785566329956055},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43303412199020386},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38454216718673706},{"id":"https://openalex.org/C139676723","wikidata":"https://www.wikidata.org/wiki/Q1193832","display_name":"Sign (mathematics)","level":2,"score":0.2991369962692261},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07564815878868103},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s41095-018-0116-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41095-018-0116-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41095-018-0116-x.pdf","source":{"id":"https://openalex.org/S2487656537","display_name":"Computational Visual Media","issn_l":"2096-0433","issn":["2096-0433","2096-0662"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Visual Media","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:2f54db85d2ca42aca4634956cdc51711","is_oa":true,"landing_page_url":"https://doaj.org/article/2f54db85d2ca42aca4634956cdc51711","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computational Visual Media, Vol 4, Iss 3, Pp 253-266 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s41095-018-0116-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41095-018-0116-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41095-018-0116-x.pdf","source":{"id":"https://openalex.org/S2487656537","display_name":"Computational Visual Media","issn_l":"2096-0433","issn":["2096-0433","2096-0662"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Visual Media","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8199999928474426,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G1014146807","display_name":null,"funder_award_id":"61772298","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320316083","display_name":"Tencent","ror":"https://ror.org/00hhjss72"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2886362581.pdf","grobid_xml":"https://content.openalex.org/works/W2886362581.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W1484210532","https://openalex.org/W1487583988","https://openalex.org/W1559773506","https://openalex.org/W1562810981","https://openalex.org/W1849277567","https://openalex.org/W1927391347","https://openalex.org/W1932624639","https://openalex.org/W2012742472","https://openalex.org/W2021383150","https://openalex.org/W2062085002","https://openalex.org/W2088049833","https://openalex.org/W2102605133","https://openalex.org/W2105529173","https://openalex.org/W2117981703","https://openalex.org/W2122710056","https://openalex.org/W2136891917","https://openalex.org/W2147527908","https://openalex.org/W2150581781","https://openalex.org/W2179352600","https://openalex.org/W2295930631","https://openalex.org/W2420613611","https://openalex.org/W2479866714","https://openalex.org/W2484169002","https://openalex.org/W2525090041","https://openalex.org/W2526468814","https://openalex.org/W2594258618","https://openalex.org/W2613718673","https://openalex.org/W2623660146","https://openalex.org/W2915043960","https://openalex.org/W2949608135","https://openalex.org/W2951548327","https://openalex.org/W2963037989","https://openalex.org/W2963542991","https://openalex.org/W2963549237","https://openalex.org/W3106250896","https://openalex.org/W3142707146","https://openalex.org/W4234552385","https://openalex.org/W4301409532","https://openalex.org/W6664298863","https://openalex.org/W6682137061","https://openalex.org/W6828894009"],"related_works":["https://openalex.org/W4382897155","https://openalex.org/W4379231512","https://openalex.org/W4283820116","https://openalex.org/W4378699879","https://openalex.org/W3128164723","https://openalex.org/W3215426395","https://openalex.org/W4286647459","https://openalex.org/W2899819381","https://openalex.org/W2557202782","https://openalex.org/W2772251146"],"abstract_inverted_index":{"Detecting":[0],"small":[1,54,65],"objects":[2],"is":[3,49,135,149,160],"a":[4,10,25,30,53,60,89],"challenging":[5],"task.":[6],"We":[7,23,105],"focus":[8],"on":[9,100,111,145,157,172],"special":[11],"case:":[12],"the":[13,80,112,118,138,173],"detection":[14,36,132,143],"and":[15,43,71,117,134,178],"classification":[16],"of":[17,41,56,82,163,185],"traffic":[18,83,90,96,122,154],"signals":[19],"in":[20,79,183],"street":[21,102],"views.":[22],"present":[24],"novel":[26],"framework":[27,144],"that":[28,64,127],"utilizes":[29],"visual":[31],"attention":[32,47],"model":[33,48],"to":[34,51,75],"make":[35],"more":[37],"efficient,":[38],"without":[39,176],"loss":[40],"accuracy,":[42],"which":[44],"generalizes.":[45],"The":[46],"designed":[50],"generate":[52],"set":[55],"candidate":[57],"regions":[58],"at":[59],"suitable":[61],"scale":[62],"so":[63],"targets":[66],"can":[67],"be":[68],"better":[69],"located":[70],"classified.":[72],"In":[73],"order":[74,162],"evaluate":[76],"our":[77,108,128],"method":[78,109,129],"context":[81],"signal":[84],"detection,":[85],"we":[86,114,169],"have":[87,106,115],"built":[88,116],"light":[91,97],"benchmark":[92],"with":[93,151],"over":[94],"15,000":[95],"instances,":[98],"based":[99],"Tencent":[101],"view":[103],"panoramas.":[104],"tested":[107,170],"both":[110,146],"dataset":[113,175],"Tsinghua\u2013Tencent":[119],"100K":[120],"(TT100K)":[121],"sign":[123,155],"benchmark.":[124],"Experiments":[125],"show":[126,167],"has":[130],"superior":[131],"performance":[133],"quicker":[136],"than":[137],"general":[139],"faster":[140],"RCNN":[141],"object":[142],"datasets.":[147],"It":[148],"competitive":[150],"state-of-the-art":[152],"specialist":[153],"detectors":[156],"TT100K,":[158],"but":[159],"an":[161,180],"magnitude":[164],"faster.":[165],"To":[166],"generality,":[168],"it":[171],"LISA":[174],"tuning,":[177],"obtained":[179],"average":[181],"precision":[182],"excess":[184],"90%.":[186]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":20},{"year":2022,"cited_by_count":16},{"year":2021,"cited_by_count":24},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":6}],"updated_date":"2026-05-22T09:01:20.584952","created_date":"2025-10-10T00:00:00"}