{"id":"https://openalex.org/W2890860133","doi":"https://doi.org/10.1109/icra.2019.8793512","title":"GANVO: Unsupervised Deep Monocular Visual Odometry and Depth Estimation with Generative Adversarial Networks","display_name":"GANVO: Unsupervised Deep Monocular Visual Odometry and Depth Estimation with Generative Adversarial Networks","publication_year":2019,"publication_date":"2019-05-01","ids":{"openalex":"https://openalex.org/W2890860133","doi":"https://doi.org/10.1109/icra.2019.8793512","mag":"2890860133"},"language":"en","primary_location":{"id":"doi:10.1109/icra.2019.8793512","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2019.8793512","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1809.05786","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Yasin Almalioglu","orcid":null},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yasin Almalioglu","raw_affiliation_strings":["Computer Science Department, The University of Oxford, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, The University of Oxford, UK","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Muhamad Risqi U. Saputra","orcid":null},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Muhamad Risqi U. Saputra","raw_affiliation_strings":["Computer Science Department, The University of Oxford, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, The University of Oxford, UK","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Pedro P. B. de Gusmao","orcid":null},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Pedro P. B. de Gusmao","raw_affiliation_strings":["Computer Science Department, The University of Oxford, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, The University of Oxford, UK","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Andrew Markham","orcid":null},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Andrew Markham","raw_affiliation_strings":["Computer Science Department, The University of Oxford, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, The University of Oxford, UK","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"last","author":{"id":null,"display_name":"Niki Trigoni","orcid":null},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Niki Trigoni","raw_affiliation_strings":["Computer Science Department, The University of Oxford, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, The University of Oxford, UK","institution_ids":["https://openalex.org/I40120149"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":141.6615,"has_fulltext":false,"cited_by_count":128,"citation_normalized_percentile":{"value":0.99948823,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"5474","last_page":"5480"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9998999834060669,"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/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/T10638","display_name":"Optical measurement and interference techniques","score":0.9969000220298767,"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-odometry","display_name":"Visual odometry","score":0.7634000182151794},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.677299976348877},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5683000087738037},{"id":"https://openalex.org/keywords/image-warping","display_name":"Image warping","score":0.5254999995231628},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.512499988079071},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.46239998936653137},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4505999982357025},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.43939998745918274},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.4101000130176544}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8532000184059143},{"id":"https://openalex.org/C5799516","wikidata":"https://www.wikidata.org/wiki/Q4110915","display_name":"Visual odometry","level":3,"score":0.7634000182151794},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6783000230789185},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.677299976348877},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5683000087738037},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5509999990463257},{"id":"https://openalex.org/C157202957","wikidata":"https://www.wikidata.org/wiki/Q1659609","display_name":"Image warping","level":2,"score":0.5254999995231628},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.512499988079071},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.46239998936653137},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4505999982357025},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.43939998745918274},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.4101000130176544},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.3643999993801117},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3109000027179718},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.31060001254081726},{"id":"https://openalex.org/C86369673","wikidata":"https://www.wikidata.org/wiki/Q1203659","display_name":"Simultaneous localization and mapping","level":4,"score":0.3075000047683716},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.30480000376701355},{"id":"https://openalex.org/C49441653","wikidata":"https://www.wikidata.org/wiki/Q2014717","display_name":"Odometry","level":4,"score":0.28929999470710754},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.28760001063346863},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.28139999508857727},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.2703999876976013},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.2694000005722046},{"id":"https://openalex.org/C2779321571","wikidata":"https://www.wikidata.org/wiki/Q7936605","display_name":"Visual learning","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.26030001044273376},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.25519999861717224},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2533000111579895}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icra.2019.8793512","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2019.8793512","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1809.05786","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1809.05786","pdf_url":"https://arxiv.org/pdf/1809.05786","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:1809.05786","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1809.05786","pdf_url":"https://arxiv.org/pdf/1809.05786","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1573897183","https://openalex.org/W1612997784","https://openalex.org/W1803059841","https://openalex.org/W1921093919","https://openalex.org/W2008706659","https://openalex.org/W2016416397","https://openalex.org/W2071499765","https://openalex.org/W2108134361","https://openalex.org/W2113014142","https://openalex.org/W2150066425","https://openalex.org/W2151290401","https://openalex.org/W2340897893","https://openalex.org/W2411454842","https://openalex.org/W2520707372","https://openalex.org/W2535547924","https://openalex.org/W2598706937","https://openalex.org/W2609883120","https://openalex.org/W2612774882","https://openalex.org/W2745549613","https://openalex.org/W2751326577","https://openalex.org/W2768662421","https://openalex.org/W2788608285","https://openalex.org/W2962891637","https://openalex.org/W2962915388","https://openalex.org/W2963583471","https://openalex.org/W2963596017","https://openalex.org/W6618872416","https://openalex.org/W6640879616","https://openalex.org/W6685261749","https://openalex.org/W6685352114","https://openalex.org/W6692550842","https://openalex.org/W6697658144","https://openalex.org/W6704970058","https://openalex.org/W6713134421","https://openalex.org/W6730329805","https://openalex.org/W6737726746","https://openalex.org/W6744150049","https://openalex.org/W6744518149","https://openalex.org/W6744864977","https://openalex.org/W6745740328"],"related_works":[],"abstract_inverted_index":{"In":[0,55],"the":[1,30,76,101,105,127,131,140],"last":[2],"decade,":[3],"supervised":[4],"deep":[5,34,84,149],"learning":[6,35,63],"approaches":[7,36],"have":[8,47],"been":[9],"extensively":[10],"employed":[11],"in":[12,21,41,52,112],"visual":[13],"odometry":[14],"(VO)":[15],"applications,":[16],"which":[17],"is":[18,26,110],"not":[19,27],"feasible":[20],"environments":[22,43],"where":[23],"labelled":[24],"data":[25,46],"abundant.":[28],"On":[29],"other":[31],"hand,":[32],"unsupervised":[33,62,148],"for":[37,155],"localization":[38],"and":[39,71,99,116,123,134,147,159],"mapping":[40],"unknown":[42],"from":[44,78],"unlabelled":[45,79],"received":[48],"comparatively":[49],"less":[50],"attention":[51],"VO":[53,150],"research.":[54],"this":[56],"study,":[57],"we":[58],"propose":[59],"a":[60,92],"generative":[61],"framework":[64,129],"that":[65,109,139],"predicts":[66],"6-DoF":[67],"pose":[68,114,157],"camera":[69],"motion":[70],"monocular":[72],"depth":[73,118,160],"map":[74],"of":[75,126],"scene":[77],"RGB":[80],"image":[81],"sequences,":[82],"using":[83],"convolutional":[85],"Generative":[86],"Adversarial":[87],"Networks":[88],"(GANs).":[89],"We":[90],"create":[91],"supervisory":[93],"signal":[94],"by":[95],"warping":[96],"view":[97],"sequences":[98],"assigning":[100],"re-projection":[102],"minimization":[103],"to":[104],"objective":[106],"loss":[107],"function":[108],"adopted":[111],"multi-view":[113],"estimation":[115,158],"single-view":[117],"generation":[119],"network.":[120],"Detailed":[121],"quantitative":[122],"qualitative":[124],"evaluations":[125],"proposed":[128,141],"on":[130],"KITTI":[132],"[1]":[133],"Cityscapes":[135],"[2]":[136],"datasets":[137],"show":[138],"method":[142],"outperforms":[143],"both":[144,156],"existing":[145],"traditional":[146],"methods":[151],"providing":[152],"better":[153],"results":[154],"recovery.":[161]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":19},{"year":2022,"cited_by_count":30},{"year":2021,"cited_by_count":23},{"year":2020,"cited_by_count":20},{"year":2019,"cited_by_count":4}],"updated_date":"2026-06-19T17:40:00.097472","created_date":"2018-09-27T00:00:00"}
