{"id":"https://openalex.org/W4406859882","doi":"https://doi.org/10.1109/vcip63160.2024.10849938","title":"AdWeatherNet: Adverse Weather Denoising with Point Cloud Spatiotemporal Attention","display_name":"AdWeatherNet: Adverse Weather Denoising with Point Cloud Spatiotemporal Attention","publication_year":2024,"publication_date":"2024-12-08","ids":{"openalex":"https://openalex.org/W4406859882","doi":"https://doi.org/10.1109/vcip63160.2024.10849938"},"language":"en","primary_location":{"id":"doi:10.1109/vcip63160.2024.10849938","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip63160.2024.10849938","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Visual Communications and Image Processing (VCIP)","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":"https://openalex.org/A5102603008","display_name":"Haozheng Han","orcid":"https://orcid.org/0009-0005-5892-0728"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"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":"Haozheng Han","raw_affiliation_strings":["Tsinghua University,Shenzhen International Graduate School,Shenzhen,China,518055"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Shenzhen International Graduate School,Shenzhen,China,518055","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043061359","display_name":"Dongyu Du","orcid":"https://orcid.org/0000-0003-2298-9721"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"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":"Dongyu Du","raw_affiliation_strings":["Tsinghua University,Shenzhen International Graduate School,Shenzhen,China,518055"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Shenzhen International Graduate School,Shenzhen,China,518055","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102981840","display_name":"Jie Luo","orcid":"https://orcid.org/0000-0002-8125-7371"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"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":"Jie Luo","raw_affiliation_strings":["Tsinghua University,Shenzhen International Graduate School,Shenzhen,China,518055"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Shenzhen International Graduate School,Shenzhen,China,518055","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023967844","display_name":"Xin Jin","orcid":"https://orcid.org/0000-0001-6655-3888"},"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"]},{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Jin","raw_affiliation_strings":["Tsinghua University,Shenzhen International Graduate School,Shenzhen,China,518055"],"affiliations":[{"raw_affiliation_string":"Tsinghua University,Shenzhen International Graduate School,Shenzhen,China,518055","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102603008"],"corresponding_institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22983238,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10930","display_name":"Flood Risk Assessment and Management","score":0.984000027179718,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10466","display_name":"Meteorological Phenomena and Simulations","score":0.982200026512146,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.621630847454071},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5868773460388184},{"id":"https://openalex.org/keywords/adverse-weather","display_name":"Adverse weather","score":0.5383350253105164},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5341068506240845},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.460050106048584},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.44711464643478394},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.4157112240791321},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2410869598388672},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1380009949207306},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.05919557809829712}],"concepts":[{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.621630847454071},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5868773460388184},{"id":"https://openalex.org/C2992147540","wikidata":"https://www.wikidata.org/wiki/Q1277161","display_name":"Adverse weather","level":2,"score":0.5383350253105164},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5341068506240845},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.460050106048584},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.44711464643478394},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.4157112240791321},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2410869598388672},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1380009949207306},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.05919557809829712},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vcip63160.2024.10849938","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip63160.2024.10849938","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8299999833106995,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1993031327","https://openalex.org/W2152864241","https://openalex.org/W2795587607","https://openalex.org/W2897876743","https://openalex.org/W2905253977","https://openalex.org/W2908808036","https://openalex.org/W2955181123","https://openalex.org/W2968296999","https://openalex.org/W2971197296","https://openalex.org/W2991216808","https://openalex.org/W3004135102","https://openalex.org/W3005974859","https://openalex.org/W3018295689","https://openalex.org/W3034543232","https://openalex.org/W3035172746","https://openalex.org/W3035574168","https://openalex.org/W3036934267","https://openalex.org/W3082942970","https://openalex.org/W3088216226","https://openalex.org/W3090139470","https://openalex.org/W3198790326","https://openalex.org/W4220824123","https://openalex.org/W4285102500","https://openalex.org/W4311437690","https://openalex.org/W4312586511","https://openalex.org/W4386075722"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4244478748","https://openalex.org/W3150465815","https://openalex.org/W4223488648","https://openalex.org/W2134969820","https://openalex.org/W2251605416","https://openalex.org/W1997222214","https://openalex.org/W2560439919","https://openalex.org/W4389340727"],"abstract_inverted_index":{"Adverse":[0],"weather":[1,93,108,172],"introduces":[2],"disruptive":[3],"noise":[4,25,33],"into":[5],"LiDAR":[6,182],"data":[7],"within":[8],"autonomous":[9,189],"driving":[10],"systems,":[11,184],"compromising":[12],"the":[13,31,65,86,96,114,125,156,160,178,186],"accuracy":[14],"and":[15,80,103,147],"range":[16],"of":[17,107,113,127,134,136,142,149,162,168,180,188],"3D":[18],"perception.":[19],"Mitigating":[20],"this":[21,48,119],"challenge":[22],"for":[23],"high-precision":[24],"removal":[26],"becomes":[27],"intricate":[28],"due":[29],"to":[30,46,78,155,177],"varying":[32],"distributions":[34],"at":[35],"different":[36],"distances.":[37],"A":[38],"novel":[39],"spatiotemporal":[40],"denoising":[41],"network,":[42],"AdWeatherNet,":[43],"is":[44],"proposed":[45],"address":[47],"problem.":[49],"The":[50,121],"Spatial":[51],"Encoder":[52],"module":[53,69],"dynamically":[54],"encodes":[55],"spatial":[56],"features":[57,100],"using":[58],"a":[59,104,131],"designed":[60],"density":[61],"evaluation":[62],"model.":[63],"Additionally,":[64],"Temporal":[66],"Differential":[67],"Attention":[68],"effectively":[70],"leverages":[71],"temporal":[72],"variation":[73],"in":[74,118,138,144,151],"adjacent":[75],"point":[76],"clouds":[77],"identify":[79],"accurately":[81],"remove":[82],"noise.":[83],"To":[84],"drive":[85],"research,":[87],"we":[88],"also":[89],"introduce":[90],"an":[91,166],"adverse":[92],"dataset,":[94,98],"named":[95],"AdScenes":[97],"which":[99],"point-wise":[101],"annotations":[102],"wide":[105],"variety":[106],"conditions,":[109],"making":[110],"it":[111],"one":[112],"largest":[115],"comprehensive":[116],"datasets":[117],"domain.":[120],"experimental":[122],"results":[123],"demonstrate":[124],"effectiveness":[126],"our":[128],"method,":[129],"with":[130],"remarkable":[132],"improvement":[133],"+9.5%":[135],"IoU":[137,143,150],"rainy":[139],"scenes,":[140,146],"+5.9%":[141],"snowy":[145],"+1.9%":[148],"foggy":[152],"scenes.":[153],"Compared":[154],"SOTA,":[157],"AdWeatherNet":[158],"enhances":[159],"mAP":[161],"object":[163],"detection":[164],"by":[165],"average":[167],"+1.8%":[169],"across":[170],"all":[171],"conditions.":[173],"Our":[174],"method":[175],"contributes":[176],"development":[179,187],"reliable":[181],"perception":[183],"fostering":[185],"vehicles.":[190]},"counts_by_year":[],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}