{"id":"https://openalex.org/W3117894272","doi":"https://doi.org/10.1109/itsc45102.2020.9294465","title":"Top-down, Spatio-Temporal Attentional Guidance for On-road Object Detection","display_name":"Top-down, Spatio-Temporal Attentional Guidance for On-road Object Detection","publication_year":2020,"publication_date":"2020-09-20","ids":{"openalex":"https://openalex.org/W3117894272","doi":"https://doi.org/10.1109/itsc45102.2020.9294465","mag":"3117894272"},"language":"en","primary_location":{"id":"doi:10.1109/itsc45102.2020.9294465","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc45102.2020.9294465","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","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/A5004947379","display_name":"Jayani Withanawasam","orcid":"https://orcid.org/0000-0002-9178-7923"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jayani Withanawasam","raw_affiliation_strings":["Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080705403","display_name":"Ehsan Javanmardi","orcid":"https://orcid.org/0000-0003-0337-115X"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ehsan Javanmardi","raw_affiliation_strings":["Institute of Industrial Science, The University of Tokyo, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Industrial Science, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109244048","display_name":"Shunsuke Kamijo","orcid":null},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shunsuke Kamijo","raw_affiliation_strings":["Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0979,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.43771306,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"84","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9994999766349792,"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":0.9930999875068665,"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":0.8075878620147705},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.7584809064865112},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7005501985549927},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6061128377914429},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5657376050949097},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5595561265945435},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5423144102096558},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.5332683324813843},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5122141242027283},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5075122117996216},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.4947318732738495},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.47520479559898376},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.45529770851135254},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.21685856580734253},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10836085677146912}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8075878620147705},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7584809064865112},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7005501985549927},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6061128377914429},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5657376050949097},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5595561265945435},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5423144102096558},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.5332683324813843},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5122141242027283},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5075122117996216},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.4947318732738495},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.47520479559898376},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.45529770851135254},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.21685856580734253},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10836085677146912},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc45102.2020.9294465","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc45102.2020.9294465","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1522301498","https://openalex.org/W1540330701","https://openalex.org/W1572655503","https://openalex.org/W1864263115","https://openalex.org/W2031489346","https://openalex.org/W2106981136","https://openalex.org/W2108598243","https://openalex.org/W2129053638","https://openalex.org/W2143828499","https://openalex.org/W2145227859","https://openalex.org/W2164084182","https://openalex.org/W2194775991","https://openalex.org/W2340897893","https://openalex.org/W2465597433","https://openalex.org/W2565639579","https://openalex.org/W2613718673","https://openalex.org/W2740110793","https://openalex.org/W2793870512","https://openalex.org/W2795812085","https://openalex.org/W2796347433","https://openalex.org/W2799352588","https://openalex.org/W2947918549","https://openalex.org/W2962858109","https://openalex.org/W2963513865","https://openalex.org/W2963542991","https://openalex.org/W2964121744","https://openalex.org/W3006929811","https://openalex.org/W4293584584","https://openalex.org/W4295312788","https://openalex.org/W6620707391","https://openalex.org/W6629368666","https://openalex.org/W6631190155","https://openalex.org/W6750227808","https://openalex.org/W6750749703","https://openalex.org/W6766978945"],"related_works":["https://openalex.org/W2069592018","https://openalex.org/W2075740387","https://openalex.org/W2357256365","https://openalex.org/W2358990940","https://openalex.org/W2348502264","https://openalex.org/W2365486383","https://openalex.org/W2362059367","https://openalex.org/W2093931120","https://openalex.org/W2901443725","https://openalex.org/W4292830139"],"abstract_inverted_index":{"On-road":[0],"object":[1,20,39,115,156],"detection":[2,21,157],"is":[3,15,57],"a":[4,24,43,58,178],"crucial":[5],"component":[6],"for":[7,29,104,134,155],"environmental":[8,125],"perception":[9],"in":[10,19,32,60,72,75,88,159],"intelligent":[11],"vehicles.":[12],"Anchor":[13],"generation":[14,151],"an":[16,140],"intermediate":[17],"step":[18],"to":[22,69,96,108,138,143],"derive":[23,139],"set":[25],"of":[26,46,113],"reference":[27],"boxes":[28],"possible":[30],"objects":[31],"different":[33],"scales":[34],"and":[35,86,128,152],"aspect":[36],"ratios.":[37],"State-of-the-art":[38],"detectors":[40],"rely":[41],"on":[42,78,82],"massive":[44],"number":[45],"pre-determined":[47],"anchors":[48],"over":[49],"the":[50,73,79,83,105,110,121,124,129,135,160,168,173],"whole":[51],"scene.":[52],"The":[53],"required":[54],"operational":[55,174],"cost":[56,175],"drawback":[59],"resource-constrained,":[61],"mobile":[62],"environments.":[63],"In":[64,117],"contrast,":[65],"humans":[66],"rapidly":[67],"attend":[68],"relevant":[70],"regions":[71],"scene":[74],"detail":[76],"based":[77],"prior":[80],"knowledge":[81,122],"current":[84],"goal":[85],"task":[87,107,137],"hand.":[89],"Inspired":[90],"by":[91],"this":[92,99],"observation,":[93],"we":[94,119,148],"aim":[95],"computationally":[97],"model":[98],"top-down":[100],"visual":[101],"attention":[102,141,162],"mechanism":[103],"driving":[106,136],"guide":[109],"anchoring":[111],"process":[112],"on-road":[114],"detection.":[116],"particular,":[118],"use":[120],"about":[123],"risk":[126,131],"level":[127],"underlying":[130],"factors":[132],"specifically":[133],"region":[142],"remain":[144],"vigilant":[145],"upon.":[146],"Then,":[147],"perform":[149],"anchor":[150],"subsequent":[153],"operations":[154],"only":[158],"extracted":[161],"region.":[163],"Experimental":[164],"results":[165],"demonstrate":[166],"that":[167],"proposed":[169],"method":[170],"significantly":[171],"reduces":[172],"while":[176],"preserving":[177],"competitive":[179],"accuracy.":[180]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}