{"id":"https://openalex.org/W2897475915","doi":"https://doi.org/10.1109/cvprw.2018.00062","title":"Visual SLAM for Automated Driving: Exploring the Applications of Deep Learning","display_name":"Visual SLAM for Automated Driving: Exploring the Applications of Deep Learning","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2897475915","doi":"https://doi.org/10.1109/cvprw.2018.00062","mag":"2897475915"},"language":"en","primary_location":{"id":"doi:10.1109/cvprw.2018.00062","doi":"https://doi.org/10.1109/cvprw.2018.00062","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw.2018.00062","pdf_url":null,"source":{"id":"https://openalex.org/S4363607748","display_name":"IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5102933058","display_name":"Stefan Milz","orcid":"https://orcid.org/0000-0002-9326-3138","observed_orcids":["https://orcid.org/0000-0002-9326-3138"]},"institutions":[{"id":"https://openalex.org/I4210112099","display_name":"Valeo (Germany)","ror":"https://ror.org/01zkeq752","country_code":"DE","type":"company","lineage":["https://openalex.org/I220619192","https://openalex.org/I4210112099"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Stefan Milz","raw_affiliation_strings":["Valeo Schalter und Sensoren GmbH"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Valeo Schalter und Sensoren GmbH","institution_ids":["https://openalex.org/I4210112099"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072132304","display_name":"Georg Arbeiter","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210112099","display_name":"Valeo (Germany)","ror":"https://ror.org/01zkeq752","country_code":"DE","type":"company","lineage":["https://openalex.org/I220619192","https://openalex.org/I4210112099"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Georg Arbeiter","raw_affiliation_strings":["Valeo Schalter und Sensoren GmbH"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Valeo Schalter und Sensoren GmbH","institution_ids":["https://openalex.org/I4210112099"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079596203","display_name":"Christian Witt","orcid":"https://orcid.org/0000-0003-0848-5367","observed_orcids":["https://orcid.org/0000-0003-0848-5367"]},"institutions":[{"id":"https://openalex.org/I4210112099","display_name":"Valeo (Germany)","ror":"https://ror.org/01zkeq752","country_code":"DE","type":"company","lineage":["https://openalex.org/I220619192","https://openalex.org/I4210112099"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Christian Witt","raw_affiliation_strings":["Valeo Schalter und Sensoren GmbH"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Valeo Schalter und Sensoren GmbH","institution_ids":["https://openalex.org/I4210112099"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Bassam Abdallah","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bassam Abdallah","raw_affiliation_strings":["Valeo Vision, Bobigny"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Valeo Vision, Bobigny","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014764449","display_name":"Senthil Kumar Yogamani","orcid":"https://orcid.org/0000-0003-3755-4245","observed_orcids":["https://orcid.org/0000-0003-3755-4245"]},"institutions":[{"id":"https://openalex.org/I4210126639","display_name":"Valeo (Ireland)","ror":"https://ror.org/031sgpn76","country_code":"IE","type":"company","lineage":["https://openalex.org/I220619192","https://openalex.org/I4210126639"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Senthil Yogamani","raw_affiliation_strings":["Valeo Vision Systems, Ireland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Valeo Vision Systems, Ireland","institution_ids":["https://openalex.org/I4210126639"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.5158,"has_fulltext":false,"cited_by_count":112,"citation_normalized_percentile":{"value":0.95299814,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"360","last_page":"36010"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9980000257492065,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9980000257492065,"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":0.0010999999940395355,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.0005000000237487257,"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/visual-slam","display_name":"visual SLAM","score":0.8389999866485596},{"id":"https://openalex.org/keywords/autonomous-driving","display_name":"autonomous driving","score":0.9760000109672546},{"id":"https://openalex.org/keywords/deep-learning","display_name":"deep learning","score":0.8930000066757202},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.8489999771118164},{"id":"https://openalex.org/keywords/depth-estimation","display_name":"depth estimation","score":0.9490000009536743},{"id":"https://openalex.org/keywords/optical-flow-prediction","display_name":"optical flow prediction","score":0.9729999899864197},{"id":"https://openalex.org/keywords/motion-segmentation","display_name":"motion segmentation","score":0.9860000014305115},{"id":"https://openalex.org/keywords/commercial-deployment","display_name":"commercial deployment","score":0.6970000267028809},{"id":"https://openalex.org/keywords/object-detection-and-recognition","display_name":"object detection and recognition","score":0.6340000033378601}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.789828896522522},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.7756209373474121},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7623164057731628},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7584564685821533},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7476620078086853},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6567855477333069},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.637503445148468},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5527530908584595},{"id":"https://openalex.org/C86369673","wikidata":"https://www.wikidata.org/wiki/Q1203659","display_name":"Simultaneous localization and mapping","level":4,"score":0.5475162863731384},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4956318140029907},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.49220290780067444},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.4165342450141907},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.33669260144233704},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.21762755513191223},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.10831239819526672},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.10596096515655518},{"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/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/cvprw.2018.00062","doi":"https://doi.org/10.1109/cvprw.2018.00062","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw.2018.00062","pdf_url":null,"source":{"id":"https://openalex.org/S4363607748","display_name":"IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":79,"referenced_works":["https://openalex.org/W360623563","https://openalex.org/W612478963","https://openalex.org/W801273237","https://openalex.org/W1523444002","https://openalex.org/W1612997784","https://openalex.org/W1664180146","https://openalex.org/W1745334888","https://openalex.org/W1875235752","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1907877624","https://openalex.org/W1921093919","https://openalex.org/W1968771169","https://openalex.org/W1992989752","https://openalex.org/W1993850091","https://openalex.org/W2002875082","https://openalex.org/W2022508996","https://openalex.org/W2033819227","https://openalex.org/W2041232406","https://openalex.org/W2076756823","https://openalex.org/W2108134361","https://openalex.org/W2109521789","https://openalex.org/W2113708607","https://openalex.org/W2124907686","https://openalex.org/W2137097255","https://openalex.org/W2150066425","https://openalex.org/W2151290401","https://openalex.org/W2152032429","https://openalex.org/W2152671441","https://openalex.org/W2163468753","https://openalex.org/W2167687475","https://openalex.org/W2171295735","https://openalex.org/W2171740948","https://openalex.org/W2171943915","https://openalex.org/W2200124539","https://openalex.org/W2259424905","https://openalex.org/W2286929393","https://openalex.org/W2300779272","https://openalex.org/W2339763956","https://openalex.org/W2340897893","https://openalex.org/W2342840547","https://openalex.org/W2431874326","https://openalex.org/W2434421859","https://openalex.org/W2435623039","https://openalex.org/W2464708700","https://openalex.org/W2474281075","https://openalex.org/W2474309084","https://openalex.org/W2517104666","https://openalex.org/W2520707372","https://openalex.org/W2556455135","https://openalex.org/W2559767995","https://openalex.org/W2560474170","https://openalex.org/W2561074213","https://openalex.org/W2562137921","https://openalex.org/W2566030665","https://openalex.org/W2579275111","https://openalex.org/W2593414960","https://openalex.org/W2598706937","https://openalex.org/W2600777408","https://openalex.org/W2606794968","https://openalex.org/W2608018946","https://openalex.org/W2609026071","https://openalex.org/W2609883120","https://openalex.org/W2755304890","https://openalex.org/W2768185495","https://openalex.org/W2779333428","https://openalex.org/W2894138533","https://openalex.org/W2950974964","https://openalex.org/W2951916398","https://openalex.org/W2962891704","https://openalex.org/W2963583471","https://openalex.org/W2963983744","https://openalex.org/W2964096383","https://openalex.org/W3100388886","https://openalex.org/W3143919370","https://openalex.org/W4300773275","https://openalex.org/W6622862201","https://openalex.org/W6673255600","https://openalex.org/W6730565506"],"related_works":["https://openalex.org/W2891299851","https://openalex.org/W4294770432","https://openalex.org/W4367321814","https://openalex.org/W3007689203","https://openalex.org/W4323020910","https://openalex.org/W4366448635","https://openalex.org/W7171543521","https://openalex.org/W7082651036","https://openalex.org/W7167688420","https://openalex.org/W4281611374"],"abstract_inverted_index":{"Deep":[0,122],"learning":[1,65],"has":[2],"become":[3],"the":[4,41,73,81,109,118],"standard":[5,90],"model":[6],"for":[7,20,51,104],"object":[8],"detection":[9],"and":[10],"recognition.":[11],"Recently,":[12],"there":[13],"is":[14],"progress":[15],"on":[16,108],"using":[17,121],"CNN":[18],"models":[19],"geometric":[21,91],"vision":[22,92],"tasks":[23],"like":[24],"depth":[25],"estimation,":[26],"optical":[27],"flow":[28],"prediction":[29],"or":[30],"motion":[31],"segmentation.":[32],"However,":[33],"Visual":[34,75,85,100],"SLAM":[35,76,86,101],"remains":[36],"to":[37,69,124],"be":[38,67],"one":[39],"of":[40,43,72,84,89,99,120],"areas":[42],"automated":[44,55,105],"driving":[45,56,106],"where":[46],"CNNs":[47],"are":[48],"not":[49],"mature":[50],"deployment":[52],"in":[53,112],"commercial":[54,113],"systems.":[57],"In":[58],"this":[59],"paper,":[60],"we":[61,79,95,116],"explore":[62],"how":[63],"deep":[64],"can":[66],"used":[68],"replace":[70],"parts":[71],"classical":[74,128],"pipeline.":[77],"Firstly,":[78],"describe":[80],"building":[82],"blocks":[83],"pipeline":[87],"composed":[88],"tasks.":[93],"Then":[94],"provide":[96],"an":[97],"overview":[98],"use":[102],"cases":[103],"based":[107],"authors'":[110],"experience":[111],"deployment.":[114],"Finally,":[115],"discuss":[117],"opportunities":[119],"Learning":[123],"improve":[125],"upon":[126],"state-of-the-art":[127],"methods.":[129]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":24},{"year":2022,"cited_by_count":17},{"year":2021,"cited_by_count":18},{"year":2020,"cited_by_count":16},{"year":2019,"cited_by_count":14}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2018-10-26T00:00:00"}