{"id":"https://openalex.org/W4403277770","doi":"https://doi.org/10.1109/lra.2024.3477292","title":"InstanceVO: Self-Supervised Semantic Visual Odometry by Using Metric Learning to Incorporate Geometrical Priors in Instance Objects","display_name":"InstanceVO: Self-Supervised Semantic Visual Odometry by Using Metric Learning to Incorporate Geometrical Priors in Instance Objects","publication_year":2024,"publication_date":"2024-10-09","ids":{"openalex":"https://openalex.org/W4403277770","doi":"https://doi.org/10.1109/lra.2024.3477292"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2024.3477292","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2024.3477292","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"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 Robotics and Automation Letters","raw_type":"journal-article"},"type":"article","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/A5076155410","display_name":"Yuanyan Xie","orcid":"https://orcid.org/0000-0002-0063-9782"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuanyan Xie","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114243485","display_name":"Junzhe Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junzhe Yang","raw_affiliation_strings":["School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034999805","display_name":"Huaidong Zhou","orcid":"https://orcid.org/0000-0002-7106-6555"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huaidong Zhou","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103215558","display_name":"Fuchun Sun","orcid":"https://orcid.org/0000-0002-4888-9326"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fuchun Sun","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5076155410"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":6.9656,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.96283345,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"9","issue":"11","first_page":"10708","last_page":"10715"},"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":0.9997000098228455,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9988999962806702,"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":0.7431749105453491},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.7374226450920105},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6606202721595764},{"id":"https://openalex.org/keywords/visual-odometry","display_name":"Visual odometry","score":0.6190944314002991},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5772510170936584},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5016434192657471},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4446978271007538},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.10474932193756104},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.05997323989868164},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.055216073989868164}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7431749105453491},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.7374226450920105},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6606202721595764},{"id":"https://openalex.org/C5799516","wikidata":"https://www.wikidata.org/wiki/Q4110915","display_name":"Visual odometry","level":3,"score":0.6190944314002991},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5772510170936584},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5016434192657471},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4446978271007538},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.10474932193756104},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.05997323989868164},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.055216073989868164},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2024.3477292","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2024.3477292","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"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 Robotics and Automation Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.49000000953674316,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G5518054540","display_name":null,"funder_award_id":"2021ZD0113801","funder_id":"https://openalex.org/F4320329860","funder_display_name":"National Science and Technology Major Project"}],"funders":[{"id":"https://openalex.org/F4320329860","display_name":"National Science and Technology Major Project","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W2115579991","https://openalex.org/W2598706937","https://openalex.org/W2609883120","https://openalex.org/W2745859992","https://openalex.org/W2808571300","https://openalex.org/W2948647700","https://openalex.org/W2963150697","https://openalex.org/W2963311282","https://openalex.org/W2982102242","https://openalex.org/W3026254524","https://openalex.org/W3041970172","https://openalex.org/W3043971245","https://openalex.org/W3106440972","https://openalex.org/W3106458387","https://openalex.org/W3176063055","https://openalex.org/W3194533273","https://openalex.org/W3200568502","https://openalex.org/W4206120224","https://openalex.org/W4226481925","https://openalex.org/W4285293965","https://openalex.org/W4317038436","https://openalex.org/W4319303303","https://openalex.org/W4319459201","https://openalex.org/W4366411247","https://openalex.org/W4383108865","https://openalex.org/W4386071703","https://openalex.org/W4387682177","https://openalex.org/W4390872059","https://openalex.org/W4390874218","https://openalex.org/W4392251979","https://openalex.org/W4402353983","https://openalex.org/W6685261749"],"related_works":["https://openalex.org/W2580650124","https://openalex.org/W4386190339","https://openalex.org/W2968424575","https://openalex.org/W3142333283","https://openalex.org/W3122088529","https://openalex.org/W3041320102","https://openalex.org/W2111669074","https://openalex.org/W2085259108","https://openalex.org/W2101730797","https://openalex.org/W2168170647"],"abstract_inverted_index":{"Visual":[0],"odometry":[1,30,39,51],"is":[2,81,115],"one":[3],"of":[4,16,58,146,157],"the":[5,14,17,56,77,88,100,144,154],"key":[6],"technologies":[7],"for":[8,149],"unmanned":[9],"ground":[10],"vehicles.":[11],"To":[12],"improve":[13],"robustness":[15],"systems":[18,40],"and":[19,41,63,76,92,119,138,152],"enable":[20],"intelligent":[21],"tasks,":[22],"researchers":[23],"introduced":[24],"learning-based":[25],"recognition":[26,42],"modules":[27,95],"into":[28],"visual":[29,38,50],"systems,":[31],"but":[32],"didn't":[33],"realize":[34],"tight":[35],"coupling":[36],"between":[37],"modules.":[43],"This":[44],"letter":[45],"proposes":[46],"a":[47,67],"self-supervised":[48],"semantic":[49],"method,":[52],"which":[53],"can":[54],"complete":[55],"tasks":[57],"ego-motion":[59],"estimation,":[60,151],"depth":[61,139],"prediction,":[62],"instance":[64,84,109],"segmentation":[65],"with":[66],"shared":[68],"encoder.":[69],"The":[70,112,122],"potential":[71],"dynamic":[72],"regions":[73],"are":[74,96,106],"removed":[75],"image":[78],"reconstruction":[79],"loss":[80,91],"rectified":[82],"by":[83],"detection":[85],"results.":[86],"Moreover,":[87],"instance-guided":[89],"triplet":[90],"cross-task":[93],"self-attention":[94],"devised":[97],"to":[98,131],"learn":[99],"geometrical":[101],"relationships":[102],"among":[103],"pixels":[104],"that":[105,126],"implied":[107],"in":[108,134],"object":[110],"priors.":[111],"proposed":[113],"method":[114,128],"validated":[116],"on":[117],"KITTI":[118],"ComplexUrban":[120],"datasets.":[121],"experimental":[123],"results":[124],"show":[125],"our":[127],"has":[129],"superiority":[130],"baseline":[132],"models":[133],"both":[135],"pose":[136,150],"estimation":[137],"prediction.":[140],"We":[141],"also":[142],"discuss":[143],"efficacy":[145],"evaluation":[147],"metrics":[148],"consider":[153],"accumulation":[155],"errors":[156],"trajectories.":[158]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3}],"updated_date":"2026-04-11T08:14:18.477133","created_date":"2025-10-10T00:00:00"}