{"id":"https://openalex.org/W3159786156","doi":"https://doi.org/10.1109/cvpr46437.2021.00122","title":"The Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depth","display_name":"The Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depth","publication_year":2021,"publication_date":"2021-06-01","ids":{"openalex":"https://openalex.org/W3159786156","doi":"https://doi.org/10.1109/cvpr46437.2021.00122","mag":"3159786156"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr46437.2021.00122","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr46437.2021.00122","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2104.14540","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103460915","display_name":"J.S. Watson","orcid":"https://orcid.org/0000-0001-7461-5663"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jamie Watson","raw_affiliation_strings":["Niantic"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Niantic","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063600180","display_name":"Oisin Mac Aodha","orcid":"https://orcid.org/0000-0002-5787-5073"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Oisin Mac Aodha","raw_affiliation_strings":["University of Edinburgh","University of Edinburgh,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Edinburgh","institution_ids":["https://openalex.org/I98677209"]},{"raw_affiliation_string":"University of Edinburgh,","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067395390","display_name":"Victor Adrian Prisacariu","orcid":"https://orcid.org/0000-0002-0630-6129"},"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":"Victor Prisacariu","raw_affiliation_strings":["Niantic","University of Oxford"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Niantic","institution_ids":[]},{"raw_affiliation_string":"University of Oxford","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038405331","display_name":"Gabriel Brostow","orcid":"https://orcid.org/0000-0001-8472-3828"},"institutions":[{"id":"https://openalex.org/I2801187875","display_name":"University College Lahore","ror":"https://ror.org/0572v5y16","country_code":"PK","type":"education","lineage":["https://openalex.org/I2801187875"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Gabriel Brostow","raw_affiliation_strings":["Niantic","UCL"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Niantic","institution_ids":[]},{"raw_affiliation_string":"UCL","institution_ids":["https://openalex.org/I2801187875"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028022598","display_name":"Michael Firman","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Michael Firman","raw_affiliation_strings":["Niantic"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Niantic","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8732,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.75272979,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1164","last_page":"1174"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":1.0,"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":1.0,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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":0.9980000257492065,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7987483143806458},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.7212226986885071},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6792275309562683},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.6789535880088806},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5907646417617798},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5673931241035461},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.5165692567825317},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5016083717346191},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.46080708503723145},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.42774614691734314},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4106540381908417},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08577015995979309}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7987483143806458},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.7212226986885071},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6792275309562683},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.6789535880088806},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5907646417617798},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5673931241035461},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.5165692567825317},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5016083717346191},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.46080708503723145},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.42774614691734314},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4106540381908417},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08577015995979309},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":8,"locations":[{"id":"doi:10.1109/cvpr46437.2021.00122","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr46437.2021.00122","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2104.14540","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2104.14540","pdf_url":"https://arxiv.org/pdf/2104.14540","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":"","raw_type":"text"},{"id":"pmh:oai:pure.ed.ac.uk:publications/9711e010-42cd-4dee-8087-4f6e12dbc2f8","is_oa":true,"landing_page_url":"https://hdl.handle.net/20.500.11820/9711e010-42cd-4dee-8087-4f6e12dbc2f8","pdf_url":"https://www.pure.ed.ac.uk/ws/files/218951326/The_Temporal_Opportunist_WATSON_DOA28022021_AFV.pdf","source":{"id":"https://openalex.org/S4406922455","display_name":"Edinburgh Research Explorer","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Watson, J, Mac Aodha, O, Prisacariu, V, Brostow, G & Firman, M 2021, The Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depth. in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. Institute of Electrical and Electronics Engineers, pp. 1164-1174, IEEE Conference on Computer Vision and Pattern Recognition 2021, 19/06/21. https://doi.org/10.1109/CVPR46437.2021.00122","raw_type":"contributionToPeriodical"},{"id":"mag:3159786156","is_oa":true,"landing_page_url":"http://arxiv.org/pdf/2104.14540.pdf","pdf_url":null,"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":"arXiv (Cornell University)","raw_type":null},{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:10150735","is_oa":false,"landing_page_url":"https://discovery.ucl.ac.uk/id/eprint/10150735/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"     In:  2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).  (pp. pp. 1164-1174).  IEEE (2021)     ","raw_type":"Proceedings paper"},{"id":"pmh:oai:ora.ox.ac.uk:uuid:2863793b-816f-47e7-b496-6c14b9fd4805","is_oa":false,"landing_page_url":"https://ora.ox.ac.uk/objects/uuid:2863793b-816f-47e7-b496-6c14b9fd4805","pdf_url":null,"source":{"id":"https://openalex.org/S4306402636","display_name":"Oxford University Research Archive (ORA) (University of Oxford)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I40120149","host_organization_name":"University of Oxford","host_organization_lineage":["https://openalex.org/I40120149"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symplectic Elements","raw_type":"Conference item"},{"id":"pmh:oai:pure.ed.ac.uk:openaire/9711e010-42cd-4dee-8087-4f6e12dbc2f8","is_oa":true,"landing_page_url":"https://www.research.ed.ac.uk/en/publications/9711e010-42cd-4dee-8087-4f6e12dbc2f8","pdf_url":null,"source":{"id":"https://openalex.org/S4306400321","display_name":"Edinburgh Research Explorer (University of Edinburgh)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I98677209","host_organization_name":"University of Edinburgh","host_organization_lineage":["https://openalex.org/I98677209"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Watson, J, Mac Aodha, O, Prisacariu, V, Brostow, G & Firman, M 2021, The Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depth. in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. Institute of Electrical and Electronics Engineers, pp. 1164-1174, IEEE Conference on Computer Vision and Pattern Recognition 2021, 19/06/21. https://doi.org/10.1109/CVPR46437.2021.00122","raw_type":"contributionToPeriodical"},{"id":"doi:10.48550/arxiv.2104.14540","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2104.14540","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2104.14540","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2104.14540","pdf_url":"https://arxiv.org/pdf/2104.14540","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":"","raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.8399999737739563,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":150,"referenced_works":["https://openalex.org/W127013308","https://openalex.org/W612478963","https://openalex.org/W764651262","https://openalex.org/W1522301498","https://openalex.org/W1905829557","https://openalex.org/W1987648924","https://openalex.org/W2044233231","https://openalex.org/W2074254947","https://openalex.org/W2108134361","https://openalex.org/W2117248802","https://openalex.org/W2117539524","https://openalex.org/W2138821028","https://openalex.org/W2150066425","https://openalex.org/W2156380531","https://openalex.org/W2169363967","https://openalex.org/W2171740948","https://openalex.org/W2194775991","https://openalex.org/W2259424905","https://openalex.org/W2336968928","https://openalex.org/W2340897893","https://openalex.org/W2422409530","https://openalex.org/W2474873602","https://openalex.org/W2520707372","https://openalex.org/W2561074213","https://openalex.org/W2604231069","https://openalex.org/W2606794968","https://openalex.org/W2608018946","https://openalex.org/W2609883120","https://openalex.org/W2625169091","https://openalex.org/W2745144057","https://openalex.org/W2751625733","https://openalex.org/W2794337790","https://openalex.org/W2794387644","https://openalex.org/W2795023265","https://openalex.org/W2796350382","https://openalex.org/W2798410215","https://openalex.org/W2799174756","https://openalex.org/W2890474520","https://openalex.org/W2894788161","https://openalex.org/W2895192073","https://openalex.org/W2896853695","https://openalex.org/W2909119029","https://openalex.org/W2910870181","https://openalex.org/W2928601293","https://openalex.org/W2935854115","https://openalex.org/W2935920407","https://openalex.org/W2942368658","https://openalex.org/W2943956032","https://openalex.org/W2949023359","https://openalex.org/W2949231300","https://openalex.org/W2949634581","https://openalex.org/W2950557037","https://openalex.org/W2951179855","https://openalex.org/W2951261569","https://openalex.org/W2951524694","https://openalex.org/W2952280228","https://openalex.org/W2952813711","https://openalex.org/W2953139137","https://openalex.org/W2958586587","https://openalex.org/W2962793285","https://openalex.org/W2962811058","https://openalex.org/W2962816904","https://openalex.org/W2963265330","https://openalex.org/W2963316641","https://openalex.org/W2963412495","https://openalex.org/W2963488291","https://openalex.org/W2963496125","https://openalex.org/W2963549785","https://openalex.org/W2963583471","https://openalex.org/W2963619659","https://openalex.org/W2963652981","https://openalex.org/W2963706662","https://openalex.org/W2963966978","https://openalex.org/W2964009301","https://openalex.org/W2964052474","https://openalex.org/W2964153986","https://openalex.org/W2964968086","https://openalex.org/W2968998169","https://openalex.org/W2969365860","https://openalex.org/W2970961333","https://openalex.org/W2971000934","https://openalex.org/W2980467688","https://openalex.org/W2981518351","https://openalex.org/W2981732213","https://openalex.org/W2982014906","https://openalex.org/W2982336381","https://openalex.org/W2983954598","https://openalex.org/W2985775862","https://openalex.org/W2995884594","https://openalex.org/W2996181357","https://openalex.org/W3014263713","https://openalex.org/W3015992905","https://openalex.org/W3023494880","https://openalex.org/W3034428934","https://openalex.org/W3034530552","https://openalex.org/W3034604951","https://openalex.org/W3036562632","https://openalex.org/W3048510980","https://openalex.org/W3060975791","https://openalex.org/W3099519461","https://openalex.org/W3100388886","https://openalex.org/W3102132650","https://openalex.org/W3104663494","https://openalex.org/W3106635087","https://openalex.org/W3107105757","https://openalex.org/W3107156787","https://openalex.org/W3107389224","https://openalex.org/W3108103523","https://openalex.org/W3110153602","https://openalex.org/W3120407065","https://openalex.org/W3171953850","https://openalex.org/W3209067313","https://openalex.org/W6605126162","https://openalex.org/W6618872416","https://openalex.org/W6631190155","https://openalex.org/W6677455522","https://openalex.org/W6682926880","https://openalex.org/W6685059715","https://openalex.org/W6685261749","https://openalex.org/W6697658144","https://openalex.org/W6703405610","https://openalex.org/W6703874418","https://openalex.org/W6721539673","https://openalex.org/W6736260464","https://openalex.org/W6742835132","https://openalex.org/W6743438356","https://openalex.org/W6750117916","https://openalex.org/W6754030187","https://openalex.org/W6754931757","https://openalex.org/W6758389134","https://openalex.org/W6758510812","https://openalex.org/W6761506325","https://openalex.org/W6761815369","https://openalex.org/W6764350350","https://openalex.org/W6767088534","https://openalex.org/W6770451861","https://openalex.org/W6771531989","https://openalex.org/W6772313301","https://openalex.org/W6772542993","https://openalex.org/W6775540007","https://openalex.org/W6776062333","https://openalex.org/W6777329727","https://openalex.org/W6780320512","https://openalex.org/W6781070145","https://openalex.org/W6782218002","https://openalex.org/W6782481010","https://openalex.org/W6785345353","https://openalex.org/W6785847386","https://openalex.org/W6786615314","https://openalex.org/W6788648398"],"related_works":["https://openalex.org/W3175682855","https://openalex.org/W2979208272","https://openalex.org/W3015992905","https://openalex.org/W2806446538","https://openalex.org/W3106190903","https://openalex.org/W2953405240","https://openalex.org/W2969556351","https://openalex.org/W2983393775","https://openalex.org/W2992344932","https://openalex.org/W3175728696","https://openalex.org/W3156862309","https://openalex.org/W2976566494","https://openalex.org/W2949835834","https://openalex.org/W2981518351","https://openalex.org/W2790107349","https://openalex.org/W2974647428","https://openalex.org/W3135861835","https://openalex.org/W2957392140","https://openalex.org/W3013099397","https://openalex.org/W2804788208"],"abstract_inverted_index":{"Self-supervised":[0],"monocular":[1,42],"depth":[2,10,100],"estimation":[3,101],"networks":[4,43],"are":[5],"trained":[6,132],"to":[7,60,98,146,167],"predict":[8],"scene":[9],"using":[11,133],"nearby":[12],"frames":[13,31,195],"as":[14],"a":[15,123,138],"supervision":[16],"signal":[17],"during":[18],"training.":[19],"However,":[20],"for":[21],"many":[22],"applications,":[23],"sequence":[24,107],"information":[25,55,88,108],"in":[26,157],"the":[27,62,86,144,148,158],"form":[28],"of":[29,41,48,85,106,160],"video":[30],"is":[32,90,114,131,153],"also":[33],"available":[34],"at":[35,109,196],"test":[36,110,197],"time.":[37,198],"The":[38],"vast":[39],"majority":[40],"do":[44],"not":[45],"make":[46,83,104],"use":[47,69,84,105,191],"this":[49],"extra":[50],"signal,":[51],"thus":[52],"ignoring":[53],"valuable":[54],"that":[56,66,89,102,130,142,181,190],"could":[57],"be":[58],"used":[59],"improve":[61],"predicted":[63],"depth.":[64],"Those":[65],"do,":[67],"either":[68],"computationally":[70],"expensive":[71],"test-time":[72],"refinement":[73],"techniques":[74],"or":[75,193],"off-the-":[76],"shelf":[77],"recurrent":[78],"networks,":[79],"which":[80],"only":[81],"indirectly":[82],"geometric":[87],"inherently":[91],"available.We":[92],"propose":[93,122],"ManyDepth,":[94],"an":[95,164],"adaptive":[96],"approach":[97,129],"dense":[99],"can":[103],"time,":[111],"when":[112,151],"it":[113,152],"available.":[115],"Taking":[116],"inspiration":[117],"from":[118],"multi-view":[119],"stereo,":[120],"we":[121,182],"deep":[124],"end-to-end":[125],"cost":[126,149],"volume":[127,150],"based":[128],"self-supervision":[134],"only.":[135],"We":[136],"present":[137],"novel":[139],"consistency":[140],"loss":[141],"encourages":[143],"network":[145],"ignore":[147],"deemed":[154],"unreliable,":[155],"e.g.":[156],"case":[159],"moving":[161],"objects,":[162],"and":[163,178],"augmentation":[165],"scheme":[166],"cope":[168],"with":[169],"static":[170],"cameras.":[171],"Our":[172],"detailed":[173],"experiments":[174],"on":[175],"both":[176],"KITTI":[177],"Cityscapes":[179],"show":[180],"outperform":[183],"all":[184],"published":[185],"self-supervised":[186],"baselines,":[187],"including":[188],"those":[189],"single":[192],"multiple":[194]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
