{"id":"https://openalex.org/W4401067481","doi":"https://doi.org/10.1145/3670105.3670152","title":"Self-supervised Recurrent Visual Odometry, Depth Estimation, and Instance Segmentation","display_name":"Self-supervised Recurrent Visual Odometry, Depth Estimation, and Instance Segmentation","publication_year":2024,"publication_date":"2024-05-24","ids":{"openalex":"https://openalex.org/W4401067481","doi":"https://doi.org/10.1145/3670105.3670152"},"language":"en","primary_location":{"id":"doi:10.1145/3670105.3670152","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3670105.3670152","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 5th International Conference on Computing, Networks and Internet of Things","raw_type":"proceedings-article"},"type":"conference-paper","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/A5104086923","display_name":"Chujia Lin","orcid":"https://orcid.org/0009-0001-6178-0501"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chujia Lin","raw_affiliation_strings":["South China University of Technology, China"],"raw_orcid":"https://orcid.org/0009-0001-6178-0501","affiliations":[{"raw_affiliation_string":"South China University of Technology, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100744924","display_name":"Yiqi Liu","orcid":"https://orcid.org/0000-0001-8911-727X"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiqi Liu","raw_affiliation_strings":["South China University of Technology, China"],"raw_orcid":"https://orcid.org/0000-0001-8911-727X","affiliations":[{"raw_affiliation_string":"South China University of Technology, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101785904","display_name":"An Chen","orcid":"https://orcid.org/0000-0002-6275-759X"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"An Chen","raw_affiliation_strings":["South China University of Technology, China"],"raw_orcid":"https://orcid.org/0000-0002-6275-759X","affiliations":[{"raw_affiliation_string":"South China University of Technology, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018505391","display_name":"Hongxia Gao","orcid":"https://orcid.org/0000-0003-4166-6864"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongxia Gao","raw_affiliation_strings":["South China University of Technology, China"],"raw_orcid":"https://orcid.org/0000-0003-4166-6864","affiliations":[{"raw_affiliation_string":"South China University of Technology, China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I90610280"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"282","last_page":"286"},"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9990000128746033,"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":0.8195518255233765},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7525331377983093},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.667414665222168},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6093727350234985},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5818018317222595},{"id":"https://openalex.org/keywords/odometry","display_name":"Odometry","score":0.49921131134033203},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4287060797214508},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36371421813964844},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.14024651050567627},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.10932379961013794}],"concepts":[{"id":"https://openalex.org/C5799516","wikidata":"https://www.wikidata.org/wiki/Q4110915","display_name":"Visual odometry","level":3,"score":0.8195518255233765},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7525331377983093},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.667414665222168},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6093727350234985},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5818018317222595},{"id":"https://openalex.org/C49441653","wikidata":"https://www.wikidata.org/wiki/Q2014717","display_name":"Odometry","level":4,"score":0.49921131134033203},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4287060797214508},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36371421813964844},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.14024651050567627},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.10932379961013794}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3670105.3670152","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3670105.3670152","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 5th International Conference on Computing, Networks and Internet of Things","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7786207935","display_name":null,"funder_award_id":"62273151, 61873096 and 62073145","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"}],"funders":[{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1905829557","https://openalex.org/W2115579991","https://openalex.org/W2150066425","https://openalex.org/W2152671441","https://openalex.org/W2300779272","https://openalex.org/W2520707372","https://openalex.org/W2609883120","https://openalex.org/W2962816904","https://openalex.org/W2963150697","https://openalex.org/W2963488291","https://openalex.org/W2963591054","https://openalex.org/W2964314455","https://openalex.org/W2985775862","https://openalex.org/W3034604951","https://openalex.org/W3041970172","https://openalex.org/W3043971245","https://openalex.org/W3102327032","https://openalex.org/W3174211490","https://openalex.org/W4300448588"],"related_works":["https://openalex.org/W2979950214","https://openalex.org/W87609089","https://openalex.org/W2414561716","https://openalex.org/W3024737167","https://openalex.org/W3161199934","https://openalex.org/W2303855011","https://openalex.org/W2312326526","https://openalex.org/W2412578866","https://openalex.org/W3105866016","https://openalex.org/W4312703710"],"abstract_inverted_index":{"Self-supervised":[0],"methods":[1,23],"for":[2,109],"monocular":[3],"visual":[4,113],"odometry":[5,114,136],"and":[6,60,87,115,138],"depth":[7,116,146],"estimation":[8],"based":[9,81],"on":[10,28,82,134,144],"deep":[11],"learning":[12],"have":[13],"recently":[14],"demonstrated":[15],"very":[16],"promising":[17],"results.":[18],"However,":[19],"most":[20],"of":[21,37,48,112],"the":[22,35,38,46,52],"are":[24],"unable":[25],"to":[26,66,93,99],"operate":[27],"image":[29,53,159],"sequences.":[30,54],"Therefore,":[31,75],"we":[32,76],"believe":[33],"that":[34,63,152],"performance":[36,128],"current":[39],"models":[40],"can":[41,119,156],"be":[42],"significantly":[43],"improved":[44],"with":[45,71,129],"help":[47],"contextual":[49],"information":[50,95],"from":[51,96],"Agents":[55],"should":[56],"possess":[57],"perceptual":[58,69],"capabilities,":[59],"an":[61],"architecture":[62],"enables":[64],"them":[65],"perform":[67,121],"multiple":[68],"tasks":[70],"a":[72,78,83,89],"single":[73],"thread.":[74],"propose":[77],"multi-task":[79],"model":[80,103,155],"shared":[84],"feature":[85],"extractor":[86],"utilize":[88],"recurrent":[90],"memory":[91],"module":[92],"transfer":[94],"previous":[97],"frames":[98],"subsequent":[100],"frames.":[101],"Our":[102,124,149],"does":[104],"not":[105],"require":[106],"any":[107],"labels":[108],"self-supervised":[110],"training":[111],"estimation.":[117],"It":[118],"also":[120],"semantic":[122],"segmentation.":[123],"method":[125],"achieves":[126],"outstanding":[127],"0.008":[130],"absolute":[131],"trajectory":[132],"error":[133,143],"KITTI":[135,145],"benchmark":[137],"4.734":[139],"root":[140],"mean":[141],"square":[142],"prediction":[147],"benchmark.":[148],"experiments":[150],"demonstrate":[151],"our":[153],"proposed":[154],"effectively":[157],"leverage":[158],"sequence":[160],"information.":[161]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}