{"id":"https://openalex.org/W7151963553","doi":"https://doi.org/10.48550/arxiv.2604.05687","title":"3D Smoke Scene Reconstruction Guided by Vision Priors from Multimodal Large Language Models","display_name":"3D Smoke Scene Reconstruction Guided by Vision Priors from Multimodal Large Language Models","publication_year":2026,"publication_date":"2026-04-07","ids":{"openalex":"https://openalex.org/W7151963553","doi":"https://doi.org/10.48550/arxiv.2604.05687"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.05687","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.05687","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.05687","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133124788","display_name":"Xinye Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Xinye","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100455899","display_name":"Fei Wang","orcid":"https://orcid.org/0009-0003-9547-5243"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Fei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133209820","display_name":"Yiqi Nie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nie, Yiqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100377549","display_name":"Kun Li","orcid":"https://orcid.org/0000-0002-5196-2096"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Kun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133195582","display_name":"Junjie Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Junjie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090052616","display_name":"Jiaqi Zhao","orcid":"https://orcid.org/0000-0002-3564-5090"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Jiaqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133154648","display_name":"Yanyan Wei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei, Yanyan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133170647","display_name":"Zhiliang Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Zhiliang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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/T11019","display_name":"Image Enhancement Techniques","score":0.595300018787384,"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/T11019","display_name":"Image Enhancement Techniques","score":0.595300018787384,"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.16210000216960907,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.09719999879598618,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.7074999809265137},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.6662999987602234},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6273000240325928},{"id":"https://openalex.org/keywords/3d-reconstruction","display_name":"3D reconstruction","score":0.5001999735832214},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4584999978542328},{"id":"https://openalex.org/keywords/3d-model","display_name":"3d model","score":0.4007999897003174},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.3801000118255615},{"id":"https://openalex.org/keywords/active-appearance-model","display_name":"Active appearance model","score":0.3310999870300293}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7883999943733215},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7415000200271606},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.715499997138977},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.7074999809265137},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.6662999987602234},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6273000240325928},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.5001999735832214},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4584999978542328},{"id":"https://openalex.org/C3019007443","wikidata":"https://www.wikidata.org/wiki/Q568742","display_name":"3d model","level":2,"score":0.4007999897003174},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.3801000118255615},{"id":"https://openalex.org/C83248878","wikidata":"https://www.wikidata.org/wiki/Q344000","display_name":"Active appearance model","level":3,"score":0.3310999870300293},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.32440000772476196},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.2930999994277954},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.2881999909877777},{"id":"https://openalex.org/C204060014","wikidata":"https://www.wikidata.org/wiki/Q6002069","display_name":"Image-based lighting","level":4,"score":0.2847000062465668},{"id":"https://openalex.org/C89720835","wikidata":"https://www.wikidata.org/wiki/Q1531701","display_name":"Global illumination","level":3,"score":0.27810001373291016},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25920000672340393},{"id":"https://openalex.org/C58874564","wikidata":"https://www.wikidata.org/wiki/Q130768","display_name":"Smoke","level":2,"score":0.257099986076355},{"id":"https://openalex.org/C2776449333","wikidata":"https://www.wikidata.org/wiki/Q7928781","display_name":"View synthesis","level":3,"score":0.2567000091075897},{"id":"https://openalex.org/C44185422","wikidata":"https://www.wikidata.org/wiki/Q6002064","display_name":"Image-based modeling and rendering","level":3,"score":0.2547999918460846},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.05687","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.05687","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.05687","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.05687","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.6267276406288147,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Reconstructing":[0],"3D":[1,39,61,80,104],"scenes":[2],"from":[3],"smoke-degraded":[4,47],"multi-view":[5],"images":[6,48],"is":[7],"particularly":[8],"difficult":[9],"because":[10],"smoke":[11,66,130],"introduces":[12,83],"strong":[13],"scattering":[14],"effects,":[15],"view-dependent":[16,86],"appearance":[17,92],"changes,":[18],"and":[19,49,56,69,82,123],"severe":[20],"degradation":[21],"of":[22,103,117],"cross-view":[23],"consistency.":[24],"To":[25],"address":[26],"these":[27],"issues,":[28],"we":[29],"propose":[30],"a":[31,59,84],"framework":[32,64],"that":[33],"integrates":[34],"visual":[35,52],"priors":[36],"with":[37],"efficient":[38],"scene":[40,67,77],"modeling.":[41],"We":[42],"employ":[43],"Nano-Banana-Pro":[44],"to":[45,89,110],"enhance":[46],"provide":[50],"clearer":[51],"observations":[53],"for":[54,65,120],"reconstruction":[55,68],"develop":[57],"Smoke-GS,":[58],"medium-aware":[60],"Gaussian":[62,105],"Splatting":[63,106],"restoration-oriented":[70],"novel":[71,126],"view":[72],"synthesis.":[73],"Smoke-GS":[74],"models":[75],"the":[76,100,115],"using":[78],"explicit":[79],"Gaussians":[81],"lightweight":[85],"medium":[87],"branch":[88],"capture":[90],"direction-dependent":[91],"variations":[93],"caused":[94],"by":[95],"smoke.":[96],"Our":[97],"method":[98,119],"preserves":[99],"rendering":[101],"efficiency":[102],"while":[107],"improving":[108],"robustness":[109],"smoke-induced":[111],"degradation.":[112],"Results":[113],"demonstrate":[114],"effectiveness":[116],"our":[118],"generating":[121],"consistent":[122],"visually":[124],"clear":[125],"views":[127],"in":[128],"challenging":[129],"environments.":[131]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-09T00:00:00"}
