{"id":"https://openalex.org/W3210856033","doi":"https://doi.org/10.1109/iv48863.2021.9575796","title":"Temporal Semantics Auto-Encoding based Moving Objects Detection in Urban Driving Scenario","display_name":"Temporal Semantics Auto-Encoding based Moving Objects Detection in Urban Driving Scenario","publication_year":2021,"publication_date":"2021-07-11","ids":{"openalex":"https://openalex.org/W3210856033","doi":"https://doi.org/10.1109/iv48863.2021.9575796","mag":"3210856033"},"language":"en","primary_location":{"id":"doi:10.1109/iv48863.2021.9575796","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv48863.2021.9575796","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 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/A5070001231","display_name":"Fahad Lateef","orcid":"https://orcid.org/0000-0002-1018-518X"},"institutions":[{"id":"https://openalex.org/I37553959","display_name":"Universit\u00e9 de technologie de belfort-montb\u00e9liard","ror":"https://ror.org/05bn3m307","country_code":"FR","type":"education","lineage":["https://openalex.org/I37553959"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Fahad Lateef","raw_affiliation_strings":["CIAD UMR 7533 UBFC, UTBM, Belfort, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CIAD UMR 7533 UBFC, UTBM, Belfort, France","institution_ids":["https://openalex.org/I37553959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077514642","display_name":"Mohamed Kas","orcid":"https://orcid.org/0000-0001-5123-4681"},"institutions":[{"id":"https://openalex.org/I37553959","display_name":"Universit\u00e9 de technologie de belfort-montb\u00e9liard","ror":"https://ror.org/05bn3m307","country_code":"FR","type":"education","lineage":["https://openalex.org/I37553959"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Mohamed Kas","raw_affiliation_strings":["CIAD UMR 7533 UBFC, UTBM, Belfort, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CIAD UMR 7533 UBFC, UTBM, Belfort, France","institution_ids":["https://openalex.org/I37553959"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083239938","display_name":"Yassine Ruichek","orcid":"https://orcid.org/0000-0003-4795-8569"},"institutions":[{"id":"https://openalex.org/I37553959","display_name":"Universit\u00e9 de technologie de belfort-montb\u00e9liard","ror":"https://ror.org/05bn3m307","country_code":"FR","type":"education","lineage":["https://openalex.org/I37553959"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Yassine Ruichek","raw_affiliation_strings":["CIAD UMR 7533 UBFC, UTBM, Belfort, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CIAD UMR 7533 UBFC, UTBM, Belfort, France","institution_ids":["https://openalex.org/I37553959"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2911,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.57132949,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1352","last_page":"1358"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9998999834060669,"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":0.9995999932289124,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8456993103027344},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7006222009658813},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6772664189338684},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6380332708358765},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.633545994758606},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6142674684524536},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5588864088058472},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.48534050583839417},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.48145025968551636},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.42022547125816345},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4192475974559784},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2044714391231537}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8456993103027344},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7006222009658813},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6772664189338684},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6380332708358765},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.633545994758606},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6142674684524536},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5588864088058472},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.48534050583839417},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.48145025968551636},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.42022547125816345},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4192475974559784},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2044714391231537},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iv48863.2021.9575796","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv48863.2021.9575796","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.8500000238418579,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320326275","display_name":"Higher Education Commision, Pakistan","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W1921093919","https://openalex.org/W2031031248","https://openalex.org/W2088285655","https://openalex.org/W2101703235","https://openalex.org/W2123277060","https://openalex.org/W2194775991","https://openalex.org/W2745012865","https://openalex.org/W2774058387","https://openalex.org/W2904631343","https://openalex.org/W2908721328","https://openalex.org/W2947465559","https://openalex.org/W2990620661","https://openalex.org/W2996010494","https://openalex.org/W2996704929","https://openalex.org/W2997671871","https://openalex.org/W3013060085","https://openalex.org/W3112421854","https://openalex.org/W3117092451","https://openalex.org/W6770458317"],"related_works":["https://openalex.org/W4390516098","https://openalex.org/W2181948922","https://openalex.org/W2384362569","https://openalex.org/W4386083130","https://openalex.org/W4205302943","https://openalex.org/W4283822356","https://openalex.org/W1950940422","https://openalex.org/W2129146436","https://openalex.org/W2032507829","https://openalex.org/W2147282173"],"abstract_inverted_index":{"Detecting":[0],"moving":[1,5,35,68,93],"objects":[2,69,125],"from":[3,57,100],"a":[4,8,89,101,114],"vehicle":[6],"is":[7,105],"challenging":[9],"problem":[10],"and":[11,47,51,59,128,164],"crucial":[12],"for":[13],"autonomous":[14],"driving,":[15],"especially":[16],"in":[17,77,159],"urban":[18],"scenarios.":[19],"The":[20],"current":[21],"literature":[22],"has":[23],"focused":[24],"on":[25,107,151],"this":[26,85],"task":[27],"as":[28],"many":[29],"approaches":[30,39],"have":[31],"been":[32],"dedicated":[33],"to":[34,65,71,79,92],"object":[36,94],"detection.":[37],"These":[38],"consist":[40],"of":[41,55,126,143,161],"multistage":[42],"pipelines,":[43],"including":[44],"semantic":[45,115],"segmentation":[46,116],"optical":[48],"flow":[49],"estimation,":[50],"require":[52],"multiple":[53],"sources":[54],"information":[56,98],"active":[58],"passive":[60],"sensors.":[61],"However,":[62],"they":[63],"fail":[64],"accurately":[66],"segment":[67],"due":[70],"the":[72,80,124,129,141],"large":[73],"ego-":[74],"camera":[75],"motion,":[76],"addition":[78],"high":[81],"processing":[82,97],"time.":[83],"In":[84],"work,":[86],"we":[87],"propose":[88],"novel":[90],"approach":[91,104],"detection":[95],"by":[96],"only":[99],"camera.":[102],"Our":[103],"based":[106],"integrating":[108],"an":[109],"encoder-decoder":[110],"network":[111],"(EDNet)":[112],"with":[113,147,166],"model":[117,146],"(Mask":[118],"R-CNN),":[119],"where":[120],"Mask":[121],"R-CNN":[122],"detects":[123],"interest":[127],"EDNet":[130],"classifies":[131],"their":[132],"motion":[133],"(moving/static)":[134],"over":[135],"two":[136],"consecutive":[137],"frames.":[138],"We":[139,155],"compare":[140],"results":[142],"our":[144],"proposed":[145],"existing":[148],"MOD":[149],"models":[150],"three":[152],"SOTA":[153,157],"benchmarks.":[154],"achieved":[156],"performance":[158],"terms":[160],"visual":[162],"quality":[163],"accuracy":[165],"competitive":[167],"speed.":[168]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
