{"id":"https://openalex.org/W4413155552","doi":"https://doi.org/10.1109/cvpr52734.2025.01506","title":"RainyGS: Efficient Rain Synthesis with Physically-Based Gaussian Splatting","display_name":"RainyGS: Efficient Rain Synthesis with Physically-Based Gaussian Splatting","publication_year":2025,"publication_date":"2025-06-10","ids":{"openalex":"https://openalex.org/W4413155552","doi":"https://doi.org/10.1109/cvpr52734.2025.01506"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr52734.2025.01506","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52734.2025.01506","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","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/A5054470711","display_name":"Qiyu Dai","orcid":"https://orcid.org/0000-0003-4659-2438"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I111483173","display_name":"King University","ror":"https://ror.org/01evb6z23","country_code":"US","type":"education","lineage":["https://openalex.org/I111483173"]}],"countries":["CN","US"],"is_corresponding":true,"raw_author_name":"Qiyu Dai","raw_affiliation_strings":["Peking University,School of Intelligence Science and Technology"],"affiliations":[{"raw_affiliation_string":"Peking University,School of Intelligence Science and Technology","institution_ids":["https://openalex.org/I111483173","https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054210995","display_name":"Xingyu Ni","orcid":"https://orcid.org/0000-0003-1127-2848"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingyu Ni","raw_affiliation_strings":["Peking University,School of Computer Science"],"affiliations":[{"raw_affiliation_string":"Peking University,School of Computer Science","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100691698","display_name":"Qiang Shen","orcid":"https://orcid.org/0000-0002-9524-2998"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I111483173","display_name":"King University","ror":"https://ror.org/01evb6z23","country_code":"US","type":"education","lineage":["https://openalex.org/I111483173"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Qianfan Shen","raw_affiliation_strings":["Peking University,School of EECS"],"affiliations":[{"raw_affiliation_string":"Peking University,School of EECS","institution_ids":["https://openalex.org/I111483173","https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010254581","display_name":"Wenzheng Chen","orcid":"https://orcid.org/0009-0008-5623-1963"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenzheng Chen","raw_affiliation_strings":["Peking University,Wangxuan Institute of Computer Technology"],"affiliations":[{"raw_affiliation_string":"Peking University,Wangxuan Institute of Computer Technology","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010714340","display_name":"Baoquan Chen","orcid":"https://orcid.org/0000-0003-4702-036X"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I111483173","display_name":"King University","ror":"https://ror.org/01evb6z23","country_code":"US","type":"education","lineage":["https://openalex.org/I111483173"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Baoquan Chen","raw_affiliation_strings":["Peking University,School of Intelligence Science and Technology"],"affiliations":[{"raw_affiliation_string":"Peking University,School of Intelligence Science and Technology","institution_ids":["https://openalex.org/I111483173","https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068024169","display_name":"Mengyu Chu","orcid":"https://orcid.org/0000-0002-7358-433X"},"institutions":[{"id":"https://openalex.org/I111483173","display_name":"King University","ror":"https://ror.org/01evb6z23","country_code":"US","type":"education","lineage":["https://openalex.org/I111483173"]},{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Mengyu Chu","raw_affiliation_strings":["Peking University,School of Intelligence Science and Technology"],"affiliations":[{"raw_affiliation_string":"Peking University,School of Intelligence Science and Technology","institution_ids":["https://openalex.org/I111483173","https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5054470711"],"corresponding_institution_ids":["https://openalex.org/I111483173","https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.7181,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.74859789,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"16153","last_page":"16162"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12163","display_name":"Aerosol Filtration and Electrostatic Precipitation","score":0.9592999815940857,"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"}},"topics":[{"id":"https://openalex.org/T12163","display_name":"Aerosol Filtration and Electrostatic Precipitation","score":0.9592999815940857,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7588451504707336},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.46648767590522766},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.336727112531662},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08462744951248169}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7588451504707336},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.46648767590522766},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.336727112531662},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08462744951248169},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr52734.2025.01506","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52734.2025.01506","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7200000286102295,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W2022566626","https://openalex.org/W2033318187","https://openalex.org/W2040692352","https://openalex.org/W2237109911","https://openalex.org/W2465881649","https://openalex.org/W2738551266","https://openalex.org/W2962793481","https://openalex.org/W2990766893","https://openalex.org/W3035172746","https://openalex.org/W3048470710","https://openalex.org/W3109585842","https://openalex.org/W3203570626","https://openalex.org/W3215769467","https://openalex.org/W4221151978","https://openalex.org/W4232290346","https://openalex.org/W4233546237","https://openalex.org/W4245344577","https://openalex.org/W4312925928","https://openalex.org/W4312961911","https://openalex.org/W4385318467","https://openalex.org/W4386047762","https://openalex.org/W4386066233","https://openalex.org/W4386066812","https://openalex.org/W4386075614","https://openalex.org/W4386075787","https://openalex.org/W4389347899","https://openalex.org/W4390872696","https://openalex.org/W4390873026","https://openalex.org/W4390972739","https://openalex.org/W4393248012","https://openalex.org/W4399574574","https://openalex.org/W4400573485","https://openalex.org/W4402704609","https://openalex.org/W4402716145","https://openalex.org/W4402716153","https://openalex.org/W4402727915","https://openalex.org/W4402753900","https://openalex.org/W4404132771","https://openalex.org/W4404524486"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"We":[0,190],"consider":[1],"the":[2,112,134,140,151],"problem":[3],"of":[4,114,136,142,162],"adding":[5],"dynamic":[6,124],"rain":[7,58,68,125,172,183,210],"effects":[8,126,173,211],"to":[9,82,97,121,187,213],"in-the-wild":[10],"scenes":[11,129,200],"in":[12,18,127],"a":[13,107],"physically-correct":[14],"manner.":[15],"Recent":[16],"advances":[17],"scene":[19,52],"modeling":[20,117],"have":[21],"made":[22],"significant":[23],"progress,":[24],"with":[25,50,130],"NeRF":[26],"and":[27,73,92,118,145,159,166,201,208],"Gaussian":[28,119,153],"Splatting":[29,120,154],"techniques":[30,149],"emerging":[31],"as":[32,56,71],"powerful":[33],"tools":[34],"for":[35,42,196],"reconstructing":[36],"complex":[37],"scenes.":[38,87],"However,":[39],"while":[40],"effective":[41],"novel":[43,108],"view":[44],"synthesis,":[45],"these":[46],"methods":[47],"typically":[48],"struggle":[49],"challenging":[51],"editing":[53],"tasks,":[54],"such":[55,70],"physics-based":[57,63,116],"simulation.":[59],"In":[60,101],"contrast,":[61],"traditional":[62],"simulations":[64,161],"can":[65,218],"generate":[66,122],"realistic":[67,158],"effects,":[69],"raindrops":[72],"splashes,":[74,165],"but":[75],"they":[76],"often":[77],"rely":[78],"on":[79],"skilled":[80],"artists":[81],"carefully":[83],"set":[84],"up":[85],"high-fidelity":[86],"This":[88],"process":[89],"lacks":[90],"flexibility":[91],"scalability,":[93],"limiting":[94],"its":[95],"applicability":[96],"broader,":[98],"open-world":[99,128],"environments.":[100],"this":[102],"work,":[103],"we":[104],"introduce":[105],"RainyGS,":[106],"approach":[109],"that":[110,192],"leverages":[111],"strengths":[113],"both":[115,197],"photorealistic,":[123],"physical":[131],"accuracy.":[132],"At":[133],"core":[135],"our":[137],"method":[138,169],"is":[139],"integration":[141],"physically-based":[143],"raindrop":[144,163],"shallow":[146],"water":[147],"simulation":[148],"within":[150],"fast":[152],"rendering":[155],"framework,":[156],"enabling":[157],"efficient":[160],"behavior,":[164],"reflections.":[167],"Our":[168],"supports":[170],"synthesizing":[171],"at":[174,221],"over":[175,182],"30":[176],"fps,":[177],"offering":[178],"users":[179],"flexible":[180],"control":[181],"intensity\u2014from":[184],"light":[185],"drizzles":[186],"heavy":[188],"downpours.":[189],"demonstrate":[191],"RainyGS":[193],"performs":[194],"effectively":[195],"real-world":[198],"outdoor":[199],"large-scale":[202],"driving":[203],"scenarios,":[204],"delivering":[205],"more":[206],"photorealistic":[207],"physically-accurate":[209],"compared":[212],"state-of-the-art":[214],"methods.":[215],"Project":[216],"page":[217],"be":[219],"found":[220],"https://pku-vcl-geometry.github.io/RainyGS/.":[222]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}
