{"id":"https://openalex.org/W7131616259","doi":"https://doi.org/10.48550/arxiv.2602.21904","title":"UNet-Based Keypoint Regression for 3D Cone Localization in Autonomous Racing","display_name":"UNet-Based Keypoint Regression for 3D Cone Localization in Autonomous Racing","publication_year":2026,"publication_date":"2026-02-25","ids":{"openalex":"https://openalex.org/W7131616259","doi":"https://doi.org/10.48550/arxiv.2602.21904"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.21904","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126942646","display_name":"Mariia Baidachna","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Baidachna, Mariia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126901328","display_name":"James Carty","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Carty, James","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005038995","display_name":"Aidan Ferguson","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ferguson, Aidan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115689720","display_name":"Joseph Agrane","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Agrane, Joseph","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126949018","display_name":"Varad Kulkarni","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kulkarni, Varad","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126861986","display_name":"Aubrey Agub","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Agub, Aubrey","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085140749","display_name":"Michael S. Baxendale","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Baxendale, Michael","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126901196","display_name":"Aaron David","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"David, Aaron","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126894906","display_name":"Rachel Horton","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Horton, Rachel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5043276597","display_name":"Elliott Atkinson","orcid":"https://orcid.org/0000-0003-4884-1135"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Atkinson, Elliott","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.305400013923645,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10653","display_name":"Robot Manipulation and Learning","score":0.305400013923645,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.14810000360012054,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.0869000032544136,"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/leverage","display_name":"Leverage (statistics)","score":0.7727000117301941},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.5613999962806702},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.531000018119812},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.5260000228881836},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39079999923706055},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.3684000074863434},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.367900013923645}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7727000117301941},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7111999988555908},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6384999752044678},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6074000000953674},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.5613999962806702},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.531000018119812},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5260000228881836},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39079999923706055},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3684000074863434},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.367900013923645},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.3249000012874603},{"id":"https://openalex.org/C30014739","wikidata":"https://www.wikidata.org/wiki/Q5159445","display_name":"Cone (formal languages)","level":2,"score":0.3027999997138977},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.28459998965263367},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.27880001068115234},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2750000059604645},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.26820001006126404},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.2614000141620636},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.2590000033378601},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2572999894618988}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.21904","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.21904","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.21904","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":"Preprint"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2602.21904","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"cone":[1,70],"localization":[2],"in":[3,8,44,84,96,125],"3D":[4],"space":[5],"is":[6],"essential":[7],"autonomous":[9,104,127],"racing":[10,128],"for":[11,53,76,123],"precise":[12],"navigation":[13],"around":[14],"the":[15,59,74,97,102,115],"track.":[16],"Approaches":[17],"that":[18],"rely":[19],"on":[20,36,56],"traditional":[21],"computer":[22],"vision":[23],"algorithms":[24],"are":[25,33,40],"sensitive":[26],"to":[27,42],"environmental":[28],"variations,":[29],"and":[30,39,73,100,120],"neural":[31,51],"networks":[32],"often":[34],"trained":[35],"limited":[37],"data":[38],"infeasible":[41],"run":[43],"real":[45],"time.":[46],"We":[47],"present":[48],"a":[49],"UNet-based":[50],"network":[52],"keypoint":[54,85],"detection":[55],"cones,":[57],"leveraging":[58],"largest":[60],"custom-labeled":[61],"dataset":[62],"we":[63,91],"have":[64],"assembled.":[65],"Our":[66,79,106],"approach":[67,119],"enables":[68],"accurate":[69],"position":[71],"estimation":[72],"potential":[75,122],"color":[77],"prediction.":[78],"model":[80],"achieves":[81],"substantial":[82],"improvements":[83],"accuracy":[86],"over":[87],"conventional":[88],"methods.":[89],"Furthermore,":[90],"leverage":[92],"our":[93],"predicted":[94],"keypoints":[95],"perception":[98],"pipeline":[99],"evaluate":[101],"end-to-end":[103],"system.":[105],"results":[107],"show":[108],"high-quality":[109],"performance":[110],"across":[111],"all":[112],"metrics,":[113],"highlighting":[114],"effectiveness":[116],"of":[117],"this":[118],"its":[121],"adoption":[124],"competitive":[126],"systems.":[129]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-02-27T00:00:00"}
