{"id":"https://openalex.org/W2995569955","doi":"https://doi.org/10.1109/tits.2021.3071886","title":"Deep Direct Visual Odometry","display_name":"Deep Direct Visual Odometry","publication_year":2021,"publication_date":"2021-04-16","ids":{"openalex":"https://openalex.org/W2995569955","doi":"https://doi.org/10.1109/tits.2021.3071886","mag":"2995569955"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2021.3071886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2021.3071886","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":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1912.05101","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002199949","display_name":"Chaoqiang Zhao","orcid":"https://orcid.org/0000-0002-3651-2177"},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chaoqiang Zhao","raw_affiliation_strings":["Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-3651-2177","affiliations":[{"raw_affiliation_string":"Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I143593769"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028570509","display_name":"Yang Tang","orcid":"https://orcid.org/0000-0002-2750-8029"},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Tang","raw_affiliation_strings":["Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-2750-8029","affiliations":[{"raw_affiliation_string":"Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I143593769"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064255140","display_name":"Qiyu Sun","orcid":"https://orcid.org/0000-0002-1401-8768"},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiyu Sun","raw_affiliation_strings":["Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-1401-8768","affiliations":[{"raw_affiliation_string":"Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I143593769"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074022699","display_name":"Athanasios V. Vasilakos","orcid":"https://orcid.org/0000-0003-1902-9877"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]},{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["AU","CN"],"is_corresponding":false,"raw_author_name":"Athanasios V. Vasilakos","raw_affiliation_strings":["School of Electrical and Data Engineering, University of Technology Sydney, Sydney, NSW, Australia","College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-1902-9877","affiliations":[{"raw_affiliation_string":"School of Electrical and Data Engineering, University of Technology Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]},{"raw_affiliation_string":"College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5002199949"],"corresponding_institution_ids":["https://openalex.org/I143593769"],"apc_list":null,"apc_paid":null,"fwci":2.9094,"has_fulltext":false,"cited_by_count":51,"citation_normalized_percentile":{"value":0.92336497,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"23","issue":"7","first_page":"7733","last_page":"7742"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","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/T10531","display_name":"Advanced Vision and Imaging","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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10638","display_name":"Optical measurement and interference techniques","score":0.9921000003814697,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8441833257675171},{"id":"https://openalex.org/keywords/visual-odometry","display_name":"Visual odometry","score":0.8399286270141602},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7094669342041016},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6931349039077759},{"id":"https://openalex.org/keywords/odometry","display_name":"Odometry","score":0.541966438293457},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.5034374594688416},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.4780343472957611},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.4769824147224426},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4283527135848999},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.4144974648952484},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32808631658554077},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.2424083948135376},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.21681028604507446}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8441833257675171},{"id":"https://openalex.org/C5799516","wikidata":"https://www.wikidata.org/wiki/Q4110915","display_name":"Visual odometry","level":3,"score":0.8399286270141602},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7094669342041016},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6931349039077759},{"id":"https://openalex.org/C49441653","wikidata":"https://www.wikidata.org/wiki/Q2014717","display_name":"Odometry","level":4,"score":0.541966438293457},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.5034374594688416},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.4780343472957611},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.4769824147224426},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4283527135848999},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.4144974648952484},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32808631658554077},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.2424083948135376},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.21681028604507446},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","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":2,"locations":[{"id":"doi:10.1109/tits.2021.3071886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2021.3071886","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:arXiv.org:1912.05101","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1912.05101","pdf_url":"https://arxiv.org/pdf/1912.05101","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1912.05101","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1912.05101","pdf_url":"https://arxiv.org/pdf/1912.05101","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.7699999809265137,"id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G3417169102","display_name":null,"funder_award_id":"20XD1401300","funder_id":"https://openalex.org/F4320335796","funder_display_name":"Program of Shanghai Academic Research Leader"},{"id":"https://openalex.org/G5789780205","display_name":null,"funder_award_id":"61988101","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7579793218","display_name":null,"funder_award_id":"61720106008","funder_id":"https://openalex.org/F4320335568","funder_display_name":"International Cooperation and Exchange Programme"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335568","display_name":"International Cooperation and Exchange Programme","ror":null},{"id":"https://openalex.org/F4320335796","display_name":"Program of Shanghai Academic Research Leader","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W612478963","https://openalex.org/W1970329928","https://openalex.org/W2015996585","https://openalex.org/W2097117768","https://openalex.org/W2097197771","https://openalex.org/W2106938558","https://openalex.org/W2115579991","https://openalex.org/W2133665775","https://openalex.org/W2200124539","https://openalex.org/W2271840356","https://openalex.org/W2474281075","https://openalex.org/W2520707372","https://openalex.org/W2535547924","https://openalex.org/W2564632156","https://openalex.org/W2598706937","https://openalex.org/W2606794968","https://openalex.org/W2609883120","https://openalex.org/W2785512290","https://openalex.org/W2830339951","https://openalex.org/W2896474523","https://openalex.org/W2934279571","https://openalex.org/W2935854115","https://openalex.org/W2939645724","https://openalex.org/W2951524694","https://openalex.org/W2951730755","https://openalex.org/W2952348863","https://openalex.org/W2953162549","https://openalex.org/W2953405240","https://openalex.org/W2962733873","https://openalex.org/W2962816904","https://openalex.org/W2963300314","https://openalex.org/W2963583471","https://openalex.org/W2963654727","https://openalex.org/W2964968086","https://openalex.org/W2968288611","https://openalex.org/W2971000934","https://openalex.org/W2999597893","https://openalex.org/W3007191641","https://openalex.org/W3008660260","https://openalex.org/W3009401911","https://openalex.org/W3015551381","https://openalex.org/W3024605442","https://openalex.org/W3034475171","https://openalex.org/W3035056458","https://openalex.org/W3035289617","https://openalex.org/W3035498256","https://openalex.org/W3041587993","https://openalex.org/W3102327032","https://openalex.org/W3105612746","https://openalex.org/W3150327674","https://openalex.org/W6767088534","https://openalex.org/W6774929742"],"related_works":["https://openalex.org/W2979950214","https://openalex.org/W87609089","https://openalex.org/W3024737167","https://openalex.org/W2414561716","https://openalex.org/W3161199934","https://openalex.org/W2303855011","https://openalex.org/W4385894109","https://openalex.org/W2312326526","https://openalex.org/W4389665464","https://openalex.org/W2412578866"],"abstract_inverted_index":{"Traditional":[0],"monocular":[1,65,87,193],"direct":[2,149,162],"visual":[3],"odometry":[4,151,164],"(DVO)":[5],"is":[6,153],"one":[7],"of":[8,17,43,59,84,90,109,159,186,204],"the":[9,15,40,69,81,91,107,110,115,130,135,157,160,173,178,184,200],"most":[10],"famous":[11],"methods":[12],"to":[13,105,155],"estimate":[14],"ego-motion":[16],"robots":[18],"and":[19,32,119,195,202,208],"map":[20],"environments":[21],"from":[22,64],"images":[23,31],"simultaneously.":[24],"However,":[25,72],"DVO":[26,145],"heavily":[27],"relies":[28],"on":[29,172],"high-quality":[30],"accurate":[33],"initial":[34],"pose":[35,111,131],"estimation":[36],"during":[37],"tracking.":[38],"With":[39],"outstanding":[41],"performance":[42],"deep":[44,51,75,148],"learning,":[45],"previous":[46,116,161,191],"works":[47],"have":[48],"shown":[49],"that":[50,177],"neural":[52],"networks":[53],"can":[54,181],"effectively":[55,182],"learn":[56],"6-DoF":[57],"(Degree":[58],"Freedom)":[60],"poses":[61],"between":[62,93],"frames":[63],"image":[66],"sequences":[67],"in":[68],"unsupervised":[70,74,126,192],"manner.":[71],"these":[73],"learning-based":[76],"frameworks":[77],"cannot":[78],"accurately":[79],"generate":[80],"full":[82],"trajectory":[83],"a":[85,121,143],"long":[86],"video":[88],"because":[89],"scale-inconsistency":[92],"each":[94],"pose.":[95],"To":[96],"address":[97],"this":[98],"problem,":[99],"we":[100],"use":[101],"several":[102],"geometric":[103],"constraints":[104,180],"improve":[106,183],"scale-consistency":[108,185],"network,":[112],"including":[113],"improving":[114],"loss":[117],"function":[118],"proposing":[120],"novel":[122,137],"scale-to-trajectory":[123],"constraint":[124,138],"for":[125],"training.":[127],"We":[128],"call":[129],"network":[132],"trained":[133],"by":[134,167],"proposed":[136,154,179],"as":[139],"TrajNet.":[140,169],"In":[141],"addition,":[142],"new":[144],"architecture,":[146],"called":[147],"sparse":[150,163],"(DDSO),":[152],"overcome":[156],"drawbacks":[158],"(DSO)":[165],"framework":[166],"embedding":[168],"Extensive":[170],"experiments":[171],"KITTI":[174],"dataset":[175],"show":[176],"TrajNet":[187,198],"when":[188],"compared":[189],"with":[190,197],"methods,":[194],"integration":[196],"makes":[199],"initialization":[201],"tracking":[203],"DSO":[205],"more":[206],"robust":[207],"accurate.":[209]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":4}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}