{"id":"https://openalex.org/W4416113930","doi":"https://doi.org/10.1109/tits.2025.3626165","title":"Color Is Not Enough: Dataset and Method for Identifying Relevant Traffic Lights in Driving Scenes","display_name":"Color Is Not Enough: Dataset and Method for Identifying Relevant Traffic Lights in Driving Scenes","publication_year":2025,"publication_date":"2025-11-11","ids":{"openalex":"https://openalex.org/W4416113930","doi":"https://doi.org/10.1109/tits.2025.3626165"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2025.3626165","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2025.3626165","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://flore.unifi.it/bitstream/2158/1460552/1/Color_Is_Not_Enough_Dataset_and_Method_for_Identifying_Relevant_Traffic_Lights_in_Driving_Scenes.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007968398","display_name":"Tomaso Trinci","orcid":"https://orcid.org/0000-0002-4052-1930"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Tomaso Trinci","raw_affiliation_strings":["Verizon Connect Research, Florence, Italy"],"affiliations":[{"raw_affiliation_string":"Verizon Connect Research, Florence, Italy","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056168149","display_name":"Simone Magistri","orcid":"https://orcid.org/0000-0002-0520-8463"},"institutions":[{"id":"https://openalex.org/I45084792","display_name":"University of Florence","ror":"https://ror.org/04jr1s763","country_code":"IT","type":"education","lineage":["https://openalex.org/I45084792"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Simone Magistri","raw_affiliation_strings":["University of Florence, Florence, Italy"],"affiliations":[{"raw_affiliation_string":"University of Florence, Florence, Italy","institution_ids":["https://openalex.org/I45084792"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030436209","display_name":"Tommaso Bianconcini","orcid":"https://orcid.org/0000-0003-3306-568X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tommaso Bianconcini","raw_affiliation_strings":["Verizon Connect Research, Florence, Italy"],"affiliations":[{"raw_affiliation_string":"Verizon Connect Research, Florence, Italy","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058185763","display_name":"Leonardo Taccari","orcid":"https://orcid.org/0000-0003-0800-4893"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Leonardo Taccari","raw_affiliation_strings":["Verizon Connect Research, Florence, Italy"],"affiliations":[{"raw_affiliation_string":"Verizon Connect Research, Florence, Italy","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024282557","display_name":"Leonardo Sarti","orcid":"https://orcid.org/0009-0008-9550-4426"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Leonardo Sarti","raw_affiliation_strings":["Verizon Connect Research, Florence, Italy"],"affiliations":[{"raw_affiliation_string":"Verizon Connect Research, Florence, Italy","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017560687","display_name":"Francesco Sambo","orcid":"https://orcid.org/0000-0002-7726-5811"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Francesco Sambo","raw_affiliation_strings":["Verizon Connect Research, Florence, Italy"],"affiliations":[{"raw_affiliation_string":"Verizon Connect Research, Florence, Italy","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5007968398"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.34394326,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"27","issue":"1","first_page":"1116","last_page":"1125"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.6197999715805054,"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":0.6197999715805054,"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":0.11860000342130661,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.030799999833106995,"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/relevance","display_name":"Relevance (law)","score":0.7450000047683716},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.704800009727478},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5795999765396118},{"id":"https://openalex.org/keywords/scarcity","display_name":"Scarcity","score":0.41510000824928284},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.4065999984741211},{"id":"https://openalex.org/keywords/road-traffic","display_name":"Road traffic","score":0.3747999966144562},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.3538999855518341}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7462000250816345},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.7450000047683716},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.704800009727478},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6230999827384949},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5795999765396118},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.41510000824928284},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.4065999984741211},{"id":"https://openalex.org/C2985695025","wikidata":"https://www.wikidata.org/wiki/Q4323994","display_name":"Road traffic","level":2,"score":0.3747999966144562},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3702999949455261},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3587000072002411},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.3538999855518341},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3370000123977661},{"id":"https://openalex.org/C6528762","wikidata":"https://www.wikidata.org/wiki/Q1574298","display_name":"Traffic sign recognition","level":4,"score":0.30630001425743103},{"id":"https://openalex.org/C2987419075","wikidata":"https://www.wikidata.org/wiki/Q8004","display_name":"Traffic signal","level":2,"score":0.2994000017642975},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2937000095844269},{"id":"https://openalex.org/C109157449","wikidata":"https://www.wikidata.org/wiki/Q7371221","display_name":"Roundabout","level":2,"score":0.28049999475479126},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2754000127315521},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2678999900817871},{"id":"https://openalex.org/C2983860417","wikidata":"https://www.wikidata.org/wiki/Q170285","display_name":"Traffic sign","level":3,"score":0.2671000063419342},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.25360000133514404}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tits.2025.3626165","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2025.3626165","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:flore.unifi.it:2158/1460552","is_oa":true,"landing_page_url":"https://hdl.handle.net/2158/1460552","pdf_url":"https://flore.unifi.it/bitstream/2158/1460552/1/Color_Is_Not_Enough_Dataset_and_Method_for_Identifying_Relevant_Traffic_Lights_in_Driving_Scenes.pdf","source":{"id":"https://openalex.org/S4306402033","display_name":"Florence Research (University of Florence)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45084792","host_organization_name":"University of Florence","host_organization_lineage":["https://openalex.org/I45084792"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:flore.unifi.it:2158/1460552","is_oa":true,"landing_page_url":"https://hdl.handle.net/2158/1460552","pdf_url":"https://flore.unifi.it/bitstream/2158/1460552/1/Color_Is_Not_Enough_Dataset_and_Method_for_Identifying_Relevant_Traffic_Lights_in_Driving_Scenes.pdf","source":{"id":"https://openalex.org/S4306402033","display_name":"Florence Research (University of Florence)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45084792","host_organization_name":"University of Florence","host_organization_lineage":["https://openalex.org/I45084792"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416113930.pdf","grobid_xml":"https://content.openalex.org/works/W4416113930.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1562810981","https://openalex.org/W1861492603","https://openalex.org/W2194775991","https://openalex.org/W2340897893","https://openalex.org/W2737202447","https://openalex.org/W2771583656","https://openalex.org/W2890748873","https://openalex.org/W2903820641","https://openalex.org/W2903959260","https://openalex.org/W2910440362","https://openalex.org/W2953711573","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2997591727","https://openalex.org/W3011667042","https://openalex.org/W3016826426","https://openalex.org/W3034971973","https://openalex.org/W3112288498","https://openalex.org/W3116192094","https://openalex.org/W3138516171","https://openalex.org/W3172752666","https://openalex.org/W4285102642","https://openalex.org/W4312753568","https://openalex.org/W4385326070","https://openalex.org/W4390100461","https://openalex.org/W4391768503","https://openalex.org/W4391770393","https://openalex.org/W4391793360","https://openalex.org/W4396214338","https://openalex.org/W4408696750","https://openalex.org/W4413018666"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"localization":[1],"and":[2,51,60,93,142,149,164,180],"classification":[3],"of":[4,47,53,68,73,112,117],"traffic":[5,25,55,91,138],"lights":[6,26],"in":[7,17,57],"driving":[8],"scenes":[9],"are":[10,27],"crucial":[11],"for":[12,29,75],"enhancing":[13],"road":[14],"scene":[15],"understanding":[16],"various":[18],"intelligent":[19],"vehicles":[20],"applications.":[21],"However,":[22],"determining":[23],"which":[24,86],"relevant":[28],"the":[30,42,49,61,70,76,100,110,121,128,150,175,178],"ego-vehicle":[31,77],"remains":[32],"an":[33,58],"under-explored":[34],"challenge.":[35],"In":[36],"this":[37],"paper,":[38],"we":[39,119],"address":[40,109],"both":[41,147],"<italic":[43,64],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[44,65,188],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">local</i>":[45],"task":[46,67],"identifying":[48],"state":[50],"relevance":[52,96],"each":[54,90],"light":[56,92,139],"image":[59],"strictly":[62],"related":[63],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">global</i>":[66],"recommending":[69],"correct":[71],"course":[72],"action":[74],"(should":[78],"it":[79],"stop?).":[80],"We":[81],"propose":[82],"a":[83,105],"novel":[84],"architecture,":[85],"not":[87,173],"only":[88],"localizes":[89],"identifies":[94],"its":[95],"with":[97,114,137],"respect":[98],"to":[99,166],"ego-vehicle,":[101],"but":[102],"also":[103],"generates":[104],"global":[106,181],"recommendation.":[107],"To":[108],"scarcity":[111],"datasets":[113],"these":[115],"types":[116],"annotations,":[118],"introduce":[120],"Verizon":[122],"Connect":[123],"Traffic":[124,152],"Light":[125,153],"Dataset":[126,154,183],"(VZC-TLD),":[127],"first":[129],"U.S.":[130],"dataset":[131],"that":[132,157,171],"provides":[133],"3,000":[134],"images":[135],"annotated":[136],"boxes,":[140],"states,":[141],"relevance.":[143],"Experimental":[144],"results":[145],"on":[146],"VZC-TLD":[148],"DriveU":[151],"(DTLD)":[155],"show":[156],"our":[158],"unified":[159],"approach":[160],"is":[161,184],"indeed":[162],"effective,":[163],"leads":[165],"significant":[167],"improvements":[168],"over":[169],"approaches":[170],"do":[172],"exploit":[174],"synergies":[176],"between":[177],"local":[179],"tasks.":[182],"available":[185],"at:":[186],"<uri":[187],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://leotac.github.io/vzc-tld</uri>":[189]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-11-11T00:00:00"}