{"id":"https://openalex.org/W7133300734","doi":"https://doi.org/10.48550/arxiv.2603.01839","title":"LEAR: Learning Edge-Aware Representations for Event-to-LiDAR Localization","display_name":"LEAR: Learning Edge-Aware Representations for Event-to-LiDAR Localization","publication_year":2026,"publication_date":"2026-03-02","ids":{"openalex":"https://openalex.org/W7133300734","doi":"https://doi.org/10.48550/arxiv.2603.01839"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.01839","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01839","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":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.01839","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5127900142","display_name":"Kuangyi Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Chen, Kuangyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127961334","display_name":"Jun Zhang (48506)","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Jun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101187746","display_name":"Yuxi Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Yuxi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128033274","display_name":"Yi Zhou (2723)","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Yi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5068079834","display_name":"Friedrich Fraundorfer","orcid":"https://orcid.org/0000-0002-5805-8892"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fraundorfer, Friedrich","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5127900142"],"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.2596000134944916,"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":0.2596000134944916,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.1565999984741211,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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":0.13330000638961792,"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/optical-flow","display_name":"Optical flow","score":0.6754999756813049},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5059000253677368},{"id":"https://openalex.org/keywords/asynchronous-communication","display_name":"Asynchronous communication","score":0.49480000138282776},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.48030000925064087},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.45669999718666077},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.4406000077724457},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.42899999022483826},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4284999966621399},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.40639999508857727}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7993999719619751},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7099000215530396},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.6754999756813049},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6460000276565552},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5059000253677368},{"id":"https://openalex.org/C151319957","wikidata":"https://www.wikidata.org/wiki/Q752739","display_name":"Asynchronous communication","level":2,"score":0.49480000138282776},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.48030000925064087},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.45669999718666077},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.4406000077724457},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.42899999022483826},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4284999966621399},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.40639999508857727},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.4011000096797943},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.35249999165534973},{"id":"https://openalex.org/C146159030","wikidata":"https://www.wikidata.org/wiki/Q7625099","display_name":"Structure from motion","level":3,"score":0.350600004196167},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.3483999967575073},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.3319000005722046},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.311599999666214},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.30979999899864197},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.3089999854564667},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.30820000171661377},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.30239999294281006},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.28700000047683716},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.2809000015258789},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2750999927520752},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.26899999380111694},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.26409998536109924}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.01839","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01839","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":"doi:10.48550/arxiv.2603.01839","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01839","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":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Event":[0],"cameras":[1],"offer":[2],"high-temporal-resolution":[3],"sensing":[4],"that":[5,56,90,104,123],"remains":[6],"reliable":[7],"under":[8],"high-speed":[9],"motion":[10,97],"and":[11,25,61,99,127,138,155],"challenging":[12,139],"lighting,":[13],"making":[14],"them":[15,81],"promising":[16],"for":[17],"localization":[18],"from":[19,46],"LiDAR":[20,36],"point":[21],"clouds":[22],"in":[23],"GPS-denied":[24],"visually":[26],"degraded":[27],"environments.":[28],"However,":[29],"aligning":[30],"sparse,":[31],"asynchronous":[32],"events":[33],"with":[34,82],"dense":[35,62],"maps":[37],"is":[38],"fundamentally":[39],"ill-posed,":[40],"as":[41,75],"direct":[42],"correspondence":[43],"estimation":[44,84],"suffers":[45],"modality":[47],"gaps.":[48],"We":[49],"propose":[50],"LEAR,":[51],"a":[52,76,86],"dual-task":[53],"learning":[54],"framework":[55],"jointly":[57],"estimates":[58],"edge":[59],"structures":[60],"event-depth":[63],"flow":[64,83,121],"fields":[65,122],"to":[66],"bridge":[67],"the":[68,96,109,146],"sensing-modality":[69],"divide.":[70],"Instead":[71],"of":[72],"treating":[73],"edges":[74],"post-hoc":[77],"aid,":[78],"LEAR":[79,141],"couples":[80],"through":[85],"cross-modal":[87],"fusion":[88],"mechanism":[89],"injects":[91],"modality-invariant":[92],"geometric":[93],"cues":[94],"into":[95],"representation,":[98],"an":[100],"iterative":[101],"refinement":[102],"strategy":[103],"enforces":[105],"mutual":[106],"consistency":[107],"between":[108],"two":[110],"tasks":[111],"over":[112,145],"multiple":[113],"update":[114],"steps.":[115],"This":[116],"synergy":[117],"produces":[118],"edge-aware,":[119],"depth-aligned":[120],"enable":[124],"more":[125],"robust":[126],"accurate":[128],"pose":[129],"recovery":[130],"via":[131],"Perspective-n-Point":[132],"(PnP)":[133],"solvers.":[134],"On":[135],"several":[136],"popular":[137],"datasets,":[140],"achieves":[142],"superior":[143],"performance":[144],"best":[147],"prior":[148],"method.":[149],"The":[150],"source":[151],"code,":[152],"trained":[153],"models,":[154],"demo":[156],"videos":[157],"are":[158],"made":[159],"publicly":[160],"available":[161],"online.":[162]},"counts_by_year":[],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2026-03-04T00:00:00"}