{"id":"https://openalex.org/W7154360270","doi":"https://doi.org/10.48550/arxiv.2604.10213","title":"ReaLiTy and LADS: A Unified Framework and Dataset Suite for LiDAR Adaptation Across Sensors and Adverse Weather Conditions","display_name":"ReaLiTy and LADS: A Unified Framework and Dataset Suite for LiDAR Adaptation Across Sensors and Adverse Weather Conditions","publication_year":2026,"publication_date":"2026-04-11","ids":{"openalex":"https://openalex.org/W7154360270","doi":"https://doi.org/10.48550/arxiv.2604.10213"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.10213","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10213","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2604.10213","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133578992","display_name":"Vivek Anand","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Anand, Vivek","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012057446","display_name":"Bharat Lohani","orcid":"https://orcid.org/0000-0001-8589-192X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lohani, Bharat","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133556114","display_name":"Rakesh Mishra","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mishra, Rakesh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133591346","display_name":"Gaurav Pandey","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pandey, Gaurav","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.6074000000953674,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.6074000000953674,"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/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.05249999836087227,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.04470000043511391,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.8616999983787537},{"id":"https://openalex.org/keywords/suite","display_name":"Suite","score":0.8281000256538391},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6079000234603882},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5623999834060669},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.4715999960899353},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.42800000309944153},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.41909998655319214},{"id":"https://openalex.org/keywords/weather-station","display_name":"Weather station","score":0.3977999985218048}],"concepts":[{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.8616999983787537},{"id":"https://openalex.org/C79581498","wikidata":"https://www.wikidata.org/wiki/Q1367530","display_name":"Suite","level":2,"score":0.8281000256538391},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6740000247955322},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6079000234603882},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5623999834060669},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5587000250816345},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.4715999960899353},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.42800000309944153},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.41909998655319214},{"id":"https://openalex.org/C2777129202","wikidata":"https://www.wikidata.org/wiki/Q190107","display_name":"Weather station","level":2,"score":0.3977999985218048},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.37560001015663147},{"id":"https://openalex.org/C2992147540","wikidata":"https://www.wikidata.org/wiki/Q1277161","display_name":"Adverse weather","level":2,"score":0.36309999227523804},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.33399999141693115},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.3287999927997589},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.3228999972343445},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30410000681877136},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.28949999809265137},{"id":"https://openalex.org/C163985040","wikidata":"https://www.wikidata.org/wiki/Q1172399","display_name":"Data acquisition","level":2,"score":0.28529998660087585},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2824999988079071},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2824000120162964},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.2791000008583069},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.27379998564720154},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.2676999866962433},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.26750001311302185},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2578999996185303}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.10213","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10213","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.10213","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10213","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"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":{"Reliable":[0],"LiDAR":[1,46,89,126],"perception":[2,130],"requires":[3],"robustness":[4],"across":[5],"sensors,":[6],"environments,":[7],"and":[8,27,53,79,113,118,128],"adverse":[9],"weather.":[10],"However,":[11],"existing":[12],"datasets":[13],"rarely":[14],"provide":[15,120],"physically":[16,59,97],"consistent":[17,77],"observations":[18],"of":[19,33,96],"the":[20,88],"same":[21],"scene":[22],"under":[23],"varying":[24],"sensor":[25,51],"configurations":[26],"weather":[28,54,74,115],"conditions,":[29],"limiting":[30],"systematic":[31],"analysis":[32],"domain":[34],"shifts.":[35],"This":[36],"work":[37],"presents":[38],"ReaLiTy,":[39],"a":[40,63,72,94,121],"unified":[41],"physics-informed":[42],"framework":[43,57],"that":[44],"transforms":[45],"data":[47],"to":[48,66,105],"match":[49],"target":[50],"specifications":[52],"conditions.":[55],"The":[56],"integrates":[58],"grounded":[60],"cues":[61],"with":[62,102],"learning-based":[64],"module":[65],"generate":[67],"realistic":[68,114],"intensity":[69],"patterns,":[70],"while":[71],"physics-based":[73],"model":[75],"introduces":[76],"geometric":[78],"radiometric":[80],"degradations.":[81],"Building":[82],"on":[83],"this":[84],"framework,":[85],"we":[86],"introduce":[87],"Adaptation":[90],"Dataset":[91],"Suite":[92],"(LADS),":[93],"collection":[95],"consistent,":[98],"transformation-ready":[99],"point":[100],"clouds":[101],"one-to-one":[103],"correspondence":[104],"original":[106],"datasets.":[107],"Experiments":[108],"demonstrate":[109],"improved":[110],"cross-domain":[111],"consistency":[112],"effects.":[116],"ReaLiTy":[117],"LADS":[119],"reproducible":[122],"foundation":[123],"for":[124],"studying":[125],"adaptation":[127],"simulation-driven":[129],"in":[131],"intelligent":[132],"transportation":[133],"systems.":[134]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-15T00:00:00"}