{"id":"https://openalex.org/W7137810915","doi":"https://doi.org/10.1609/aaai.v40i10.37802","title":"WeatherEdit: Controllable Weather Editing with 4D Gaussian Field","display_name":"WeatherEdit: Controllable Weather Editing with 4D Gaussian Field","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7137810915","doi":"https://doi.org/10.1609/aaai.v40i10.37802"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i10.37802","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i10.37802","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1609/aaai.v40i10.37802","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129740275","display_name":"Chenghao Qian","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Chenghao Qian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129725927","display_name":"Wenjing Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wenjing Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074229836","display_name":"Yuhu Guo","orcid":"https://orcid.org/0009-0007-5398-6845"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuhu Guo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5019237761","display_name":"Gustav Markkula","orcid":"https://orcid.org/0000-0003-0244-1582"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gustav Markkula","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5129740275"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"40","issue":"10","first_page":"8511","last_page":"8519"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.5522000193595886,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.5522000193595886,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T11019","display_name":"Image Enhancement Techniques","score":0.23649999499320984,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.0754999965429306,"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/numerical-weather-prediction","display_name":"Numerical weather prediction","score":0.5759999752044678},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.54830002784729},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5321999788284302},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.38519999384880066},{"id":"https://openalex.org/keywords/weather-forecasting","display_name":"Weather forecasting","score":0.38420000672340393},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.3783999979496002},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.3727000057697296},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.3691999912261963}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6955999732017517},{"id":"https://openalex.org/C147947694","wikidata":"https://www.wikidata.org/wiki/Q837552","display_name":"Numerical weather prediction","level":2,"score":0.5759999752044678},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.54830002784729},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5321999788284302},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.38519999384880066},{"id":"https://openalex.org/C21001229","wikidata":"https://www.wikidata.org/wiki/Q182868","display_name":"Weather forecasting","level":2,"score":0.38420000672340393},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.3783999979496002},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3727000057697296},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3691999912261963},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.3433000147342682},{"id":"https://openalex.org/C138410489","wikidata":"https://www.wikidata.org/wiki/Q478751","display_name":"Surface weather observation","level":3,"score":0.34290000796318054},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32350000739097595},{"id":"https://openalex.org/C205537798","wikidata":"https://www.wikidata.org/wiki/Q1277161","display_name":"Extreme weather","level":3,"score":0.31369999051094055},{"id":"https://openalex.org/C92237259","wikidata":"https://www.wikidata.org/wiki/Q863343","display_name":"Weather radar","level":3,"score":0.2996000051498413},{"id":"https://openalex.org/C2992147540","wikidata":"https://www.wikidata.org/wiki/Q1277161","display_name":"Adverse weather","level":2,"score":0.2994999885559082},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.2842999994754791},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.27730000019073486},{"id":"https://openalex.org/C133204551","wikidata":"https://www.wikidata.org/wiki/Q838305","display_name":"Weather Research and Forecasting Model","level":2,"score":0.27140000462532043},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.26579999923706055},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2538999915122986}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i10.37802","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i10.37802","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i10.37802","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i10.37802","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.4104563593864441}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"this":[1],"work,":[2],"we":[3,43,71,102,152],"present":[4],"WeatherEdit,":[5],"a":[6,54,73,80,105,115],"novel":[7],"weather":[8,14,32,36,40,51,63,100,145,168,181],"editing":[9,34,91],"pipeline":[10],"for":[11,190],"generating":[12],"realistic":[13,144,167],"effects":[15,64,182],"with":[16,158,183],"controllable":[17,184],"types":[18],"and":[19,35,86,94,112,123,130,140,147,165],"severity":[20,149],"in":[21,65,125,194],"3D":[22,106,160],"scenes.":[23],"Our":[24],"approach":[25],"is":[26],"structured":[27],"into":[28,53],"two":[29],"key":[30],"components:":[31],"background":[33,41],"particle":[37],"construction.":[38],"For":[39],"editing,":[42],"introduce":[44,114],"an":[45],"all-in-one":[46],"adapter":[47],"that":[48,78,176],"integrates":[49],"multiple":[50,172],"styles":[52],"single":[55],"diffusion":[56],"model,":[57],"enabling":[58],"the":[59,99,109,126,154,159],"generation":[60],"of":[61,132],"diverse":[62,180],"2D":[66],"image":[67],"backgrounds.":[68],"During":[69],"inference,":[70],"design":[72],"Temporal-View":[74],"(TV-)":[75],"attention":[76],"mechanism":[77],"follows":[79],"specific":[81],"order":[82],"to":[83,119,162],"aggregate":[84],"temporal":[85],"spatial":[87],"information,":[88],"ensuring":[89,143],"consistent":[90,164],"across":[92],"multi-frame":[93],"multi-view":[95],"images.":[96],"To":[97],"construct":[98],"particles,":[101],"first":[103],"reconstruct":[104],"scene":[107,161],"using":[108],"edited":[110],"images":[111],"then":[113],"4D":[116,155],"Gaussian":[117,156],"field":[118,157],"generate":[120,179],"snowflakes,":[121],"raindrops":[122],"fog":[124],"scene.":[127],"The":[128],"attributes":[129],"dynamics":[131],"these":[133],"particles":[134],"are":[135],"controlled":[136],"through":[137],"attribute":[138],"modelling":[139],"dynamic":[141],"simulation,":[142],"representation":[146],"flexible":[148],"adjustments.":[150],"Finally,":[151],"integrate":[153],"render":[163],"highly":[166],"effects.":[169],"Experiments":[170],"on":[171],"driving":[173,192],"datasets":[174],"demonstrate":[175],"WeatherEdit":[177],"can":[178],"condition":[185],"severity,":[186],"highlighting":[187],"its":[188],"potential":[189],"autonomous":[191],"simulation":[193],"adverse":[195],"weather.":[196]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-21T09:19:25.381259","created_date":"2026-03-18T00:00:00"}
