{"id":"https://openalex.org/W4286285563","doi":"https://doi.org/10.1109/iv51971.2022.9827298","title":"Enhancement of Target Feature Regions and Intention-Driven Visual Attention Selection in Traffic Scenes","display_name":"Enhancement of Target Feature Regions and Intention-Driven Visual Attention Selection in Traffic Scenes","publication_year":2022,"publication_date":"2022-06-05","ids":{"openalex":"https://openalex.org/W4286285563","doi":"https://doi.org/10.1109/iv51971.2022.9827298"},"language":"en","primary_location":{"id":"doi:10.1109/iv51971.2022.9827298","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv51971.2022.9827298","pdf_url":null,"source":{"id":"https://openalex.org/S4363605370","display_name":"2022 IEEE Intelligent Vehicles Symposium (IV)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Intelligent Vehicles Symposium (IV)","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/A5100406570","display_name":"Jing Li","orcid":"https://orcid.org/0009-0006-5682-5150"},"institutions":[{"id":"https://openalex.org/I4610292","display_name":"Xiangtan University","ror":"https://ror.org/00xsfaz62","country_code":"CN","type":"education","lineage":["https://openalex.org/I4610292"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Li","raw_affiliation_strings":["Xiangtan University,College of Automation and Electronic Information,Xiangtan,China,411105"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xiangtan University,College of Automation and Electronic Information,Xiangtan,China,411105","institution_ids":["https://openalex.org/I4610292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100657432","display_name":"Dongbo Zhang","orcid":"https://orcid.org/0000-0003-3776-3426"},"institutions":[{"id":"https://openalex.org/I4610292","display_name":"Xiangtan University","ror":"https://ror.org/00xsfaz62","country_code":"CN","type":"education","lineage":["https://openalex.org/I4610292"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongbo Zhang","raw_affiliation_strings":["Xiangtan University,College of Automation and Electronic Information,Xiangtan,China,411105"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xiangtan University,College of Automation and Electronic Information,Xiangtan,China,411105","institution_ids":["https://openalex.org/I4610292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006195230","display_name":"Bumin Meng","orcid":"https://orcid.org/0000-0002-1266-6913"},"institutions":[{"id":"https://openalex.org/I4610292","display_name":"Xiangtan University","ror":"https://ror.org/00xsfaz62","country_code":"CN","type":"education","lineage":["https://openalex.org/I4610292"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bumin Meng","raw_affiliation_strings":["Xiangtan University,College of Automation and Electronic Information,Xiangtan,China,411105"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xiangtan University,College of Automation and Electronic Information,Xiangtan,China,411105","institution_ids":["https://openalex.org/I4610292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100694756","display_name":"Renjie Chen","orcid":"https://orcid.org/0000-0001-8395-4392"},"institutions":[{"id":"https://openalex.org/I4610292","display_name":"Xiangtan University","ror":"https://ror.org/00xsfaz62","country_code":"CN","type":"education","lineage":["https://openalex.org/I4610292"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Renjie Chen","raw_affiliation_strings":["Xiangtan University,College of Automation and Electronic Information,Xiangtan,China,411105"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xiangtan University,College of Automation and Electronic Information,Xiangtan,China,411105","institution_ids":["https://openalex.org/I4610292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008802390","display_name":"Jiajun Tang","orcid":"https://orcid.org/0000-0002-0254-9764"},"institutions":[{"id":"https://openalex.org/I4610292","display_name":"Xiangtan University","ror":"https://ror.org/00xsfaz62","country_code":"CN","type":"education","lineage":["https://openalex.org/I4610292"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiajun Tang","raw_affiliation_strings":["Xiangtan University,College of Automation and Electronic Information,Xiangtan,China,411105"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xiangtan University,College of Automation and Electronic Information,Xiangtan,China,411105","institution_ids":["https://openalex.org/I4610292"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025640070","display_name":"Yaonan Wang","orcid":"https://orcid.org/0000-0002-0519-6458"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaonan Wang","raw_affiliation_strings":["Hunan University,National Engineering Laboratory for Robot Visual Perception and Control Technology,Changsha,China,410082"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hunan University,National Engineering Laboratory for Robot Visual Perception and Control Technology,Changsha,China,410082","institution_ids":["https://openalex.org/I16609230"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05409243,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"404","last_page":"410"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9994000196456909,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9994000196456909,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9976000189781189,"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9627000093460083,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/discriminative-model","display_name":"Discriminative model","score":0.7899348139762878},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7494596838951111},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7080696821212769},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6712281703948975},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.6398220062255859},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5594456195831299},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5575898289680481},{"id":"https://openalex.org/keywords/visual-attention","display_name":"Visual attention","score":0.5387391448020935},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4899539053440094},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.43692725896835327},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.41889631748199463},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.38304659724235535},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3251485824584961},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.11646828055381775}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7899348139762878},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7494596838951111},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7080696821212769},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6712281703948975},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.6398220062255859},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5594456195831299},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5575898289680481},{"id":"https://openalex.org/C2986089797","wikidata":"https://www.wikidata.org/wiki/Q6501338","display_name":"Visual attention","level":3,"score":0.5387391448020935},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4899539053440094},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.43692725896835327},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.41889631748199463},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38304659724235535},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3251485824584961},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.11646828055381775},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iv51971.2022.9827298","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv51971.2022.9827298","pdf_url":null,"source":{"id":"https://openalex.org/S4363605370","display_name":"2022 IEEE Intelligent Vehicles Symposium (IV)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.5699999928474426}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W2099695159","https://openalex.org/W2115579991","https://openalex.org/W2126628495","https://openalex.org/W2152417180","https://openalex.org/W2154058452","https://openalex.org/W2165728411","https://openalex.org/W2221625691","https://openalex.org/W2295107390","https://openalex.org/W2314032274","https://openalex.org/W2606462007","https://openalex.org/W2740110793","https://openalex.org/W2743353723","https://openalex.org/W2776207810","https://openalex.org/W2887806157","https://openalex.org/W2947918549","https://openalex.org/W2962858109","https://openalex.org/W2963513865","https://openalex.org/W2963715038","https://openalex.org/W2997475397","https://openalex.org/W2998508940","https://openalex.org/W3009130550","https://openalex.org/W3035253074","https://openalex.org/W3100100339","https://openalex.org/W3101609372","https://openalex.org/W4211165038","https://openalex.org/W4300235091","https://openalex.org/W6738549535","https://openalex.org/W6752170072","https://openalex.org/W6754127638","https://openalex.org/W6771938857"],"related_works":["https://openalex.org/W2180954594","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W2052835778","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2049003611","https://openalex.org/W1612029326","https://openalex.org/W2510961579"],"abstract_inverted_index":{"Selective":[0],"attention":[1,37,60,93,108,111,131,156,192],"to":[2,9,19,27,52,112,128,132,157],"specific":[3,6],"areas":[4],"and":[5,105,109,163,180],"targets":[7],"according":[8],"driving":[10],"intention":[11],"is":[12,71,87,126],"of":[13,45,56,84,116,167,182],"great":[14],"significance":[15],"for":[16],"autonomous":[17],"vehicles":[18],"efficiently":[20],"obtain":[21],"external":[22,47],"environment":[23],"information.":[24],"In":[25,73],"order":[26,51],"achieve":[28],"efficient":[29],"environmental":[30],"perception,":[31],"we":[32],"propose":[33],"an":[34],"intention-driven":[35],"visual":[36],"selection":[38],"model":[39,153,184],"by":[40,95,101,138],"simulating":[41],"human":[42],"active":[43],"perception":[44],"the":[46,54,57,97,114,121,124,133,140,149,152,158,165,177],"environment.":[48],"Meanwhile,":[49],"in":[50,144],"improve":[53,113],"integrity":[55,179],"target":[58,92,117],"category":[59,118],"heatmap,":[61],"a":[62],"deep":[63],"network":[64,125],"training":[65,145],"method":[66],"with":[67,189],"feature":[68,98,110,161,168],"region":[69,137,169],"enhancement":[70],"proposed.":[72,88],"this":[74],"paper,":[75],"FIMF":[76],"Score-CAM":[77],"which":[78,147],"can":[79],"fast":[80],"integrate":[81],"multiple":[82],"features":[83],"local":[85],"space":[86],"It":[89],"generates":[90],"intention-related":[91],"map":[94,99],"weighting":[96],"extracted":[100],"forward":[102],"convolution":[103],"calculation,":[104],"combines":[106],"spatial":[107],"ability":[115],"location.":[119],"At":[120],"same":[122],"time,":[123],"forced":[127],"pay":[129],"more":[130,134],"comprehensive":[135],"target-related":[136],"using":[139],"guided":[141],"random":[142],"erasing":[143],"process,":[146],"overcomes":[148],"deficiency":[150],"that":[151,176],"only":[154],"pays":[155],"most":[159],"discriminative":[160],"region,":[162],"achieves":[164],"purpose":[166],"enhancement.":[170],"Experiments":[171],"on":[172],"KITTI":[173],"dataset":[174],"show":[175],"positioning":[178],"accuracy":[181],"our":[183],"are":[185],"significantly":[186],"improved":[187],"compared":[188],"other":[190],"top-down":[191],"models.":[193]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}