{"id":"https://openalex.org/W7128646193","doi":"https://doi.org/10.1109/icves65691.2025.11376500","title":"LiDAR Point Cloud Image-based Generation Using Denoising Diffusion Probabilistic Models","display_name":"LiDAR Point Cloud Image-based Generation Using Denoising Diffusion Probabilistic Models","publication_year":2025,"publication_date":"2025-10-27","ids":{"openalex":"https://openalex.org/W7128646193","doi":"https://doi.org/10.1109/icves65691.2025.11376500"},"language":null,"primary_location":{"id":"doi:10.1109/icves65691.2025.11376500","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icves65691.2025.11376500","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","raw_type":"proceedings-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":null,"display_name":"Amirhesam Aghanouri","orcid":null},"institutions":[{"id":"https://openalex.org/I121883995","display_name":"Johannes Kepler University of Linz","ror":"https://ror.org/052r2xn60","country_code":"AT","type":"education","lineage":["https://openalex.org/I121883995"]}],"countries":["AT"],"is_corresponding":true,"raw_author_name":"Amirhesam Aghanouri","raw_affiliation_strings":["Johannes Kepler University,Linz,Austria"],"affiliations":[{"raw_affiliation_string":"Johannes Kepler University,Linz,Austria","institution_ids":["https://openalex.org/I121883995"]}]},{"author_position":"last","author":{"id":null,"display_name":"Cristina Olaverri-Monreal","orcid":null},"institutions":[{"id":"https://openalex.org/I121883995","display_name":"Johannes Kepler University of Linz","ror":"https://ror.org/052r2xn60","country_code":"AT","type":"education","lineage":["https://openalex.org/I121883995"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Cristina Olaverri-Monreal","raw_affiliation_strings":["Johannes Kepler University,Linz,Austria"],"affiliations":[{"raw_affiliation_string":"Johannes Kepler University,Linz,Austria","institution_ids":["https://openalex.org/I121883995"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I121883995"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.73591219,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"263","last_page":"268"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.4269999861717224,"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":0.4269999861717224,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.1704999953508377,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.03849999979138374,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.737500011920929},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6858999729156494},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6118000149726868},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5730000138282776},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5133000016212463},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.4075999855995178},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.3691999912261963},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.34279999136924744}],"concepts":[{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.737500011920929},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7200000286102295},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6858999729156494},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6118000149726868},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5730000138282776},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5133000016212463},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45879998803138733},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4146000146865845},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.4075999855995178},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.39570000767707825},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3691999912261963},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.34279999136924744},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34049999713897705},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.32919999957084656},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.328000009059906},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.32249999046325684},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.32100000977516174},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.31439998745918274},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.3021000027656555},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2948000133037567},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.26649999618530273},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.2646999955177307}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icves65691.2025.11376500","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icves65691.2025.11376500","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2146950091","https://openalex.org/W2991216808","https://openalex.org/W3003437478","https://openalex.org/W3003474258","https://openalex.org/W3036627429","https://openalex.org/W3203597819","https://openalex.org/W4312739686","https://openalex.org/W4386076299","https://openalex.org/W4393638454","https://openalex.org/W4402703082"],"related_works":[],"abstract_inverted_index":{"Autonomous":[0],"vehicles":[1],"(AVs)":[2],"are":[3],"expected":[4],"to":[5,33,69,93,127],"revolutionize":[6],"transportation":[7],"by":[8,64],"improving":[9,101],"efficiency":[10],"and":[11,25,51,61,66,89,120,149,172,181,193],"safety.":[12],"Their":[13],"success":[14],"relies":[15],"on":[16,134],"3D":[17],"vision":[18,108],"systems":[19],"that":[20],"effectively":[21],"sense":[22],"the":[23,117,121,135,147,164,177],"environment":[24],"detect":[26],"traffic":[27],"agents.":[28],"Among":[29],"sensors":[30],"AVs":[31],"use":[32],"create":[34],"a":[35,78,104],"comprehensive":[36],"view":[37],"of":[38,106,179],"surroundings,":[39],"LiDAR":[40,57,183],"provides":[41],"high-resolution":[42],"depth":[43],"data":[44,58,97],"enabling":[45],"accurate":[46],"object":[47],"detection,":[48],"safe":[49],"navigation,":[50],"collision":[52],"avoidance.":[53],"However,":[54],"collecting":[55],"real-world":[56],"is":[59],"time-consuming":[60],"often":[62],"affected":[63],"noise":[65,87],"sparsity":[67],"due":[68],"adverse":[70],"weather":[71],"or":[72],"sensor":[73],"limitations.":[74],"This":[75],"work":[76],"applies":[77],"denoising":[79,118],"diffusion":[80],"probabilistic":[81],"model":[82],"(DDPM),":[83],"enhanced":[84],"with":[85,152,189],"novel":[86],"scheduling":[88],"time-step":[90],"embedding":[91],"techniques":[92],"generate":[94],"high-quality":[95],"synthetic":[96],"for":[98],"augmentation,":[99],"thereby":[100],"performance":[102,154,167],"across":[103],"range":[105],"computer":[107],"tasks,":[109],"particularly":[110],"in":[111,175],"AV":[112],"perception.":[113],"These":[114],"modifications":[115],"impact":[116],"process":[119],"model\u2019s":[122,165],"temporal":[123],"awareness,":[124],"allowing":[125],"it":[126],"produce":[128],"more":[129],"realistic":[130],"point":[131,187],"clouds":[132,188],"based":[133],"projection.":[136],"The":[137,161],"proposed":[138],"method":[139],"was":[140],"extensively":[141],"evaluated":[142],"under":[143],"various":[144],"configurations":[145],"using":[146],"IAMCV":[148],"KITTI-360":[150],"datasets,":[151],"four":[153],"metrics":[155],"compared":[156],"against":[157],"state-of-the-art":[158],"(SOTA)":[159],"methods.":[160],"results":[162],"demonstrate":[163],"superior":[166],"over":[168],"most":[169],"existing":[170],"baselines":[171],"its":[173],"effectiveness":[174],"mitigating":[176],"effects":[178],"noisy":[180],"sparse":[182],"data,":[184],"producing":[185],"diverse":[186],"rich":[190],"spatial":[191],"relationships":[192],"structural":[194],"detail.":[195]},"counts_by_year":[],"updated_date":"2026-02-13T13:36:01.753593","created_date":"2025-12-10T00:00:00"}
