{"id":"https://openalex.org/W7165668628","doi":"https://doi.org/10.48550/arxiv.2606.21898","title":"Mesh2GS: White-Box 3DGS Construction via Plenoptic Sampling","display_name":"Mesh2GS: White-Box 3DGS Construction via Plenoptic Sampling","publication_year":2026,"publication_date":"2026-06-20","ids":{"openalex":"https://openalex.org/W7165668628","doi":"https://doi.org/10.48550/arxiv.2606.21898"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.21898","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.21898","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.2606.21898","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058268359","display_name":"Hao Zhu","orcid":"https://orcid.org/0000-0003-4411-0933"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Haoran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139174277","display_name":"Youcheng Cai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cai, Youcheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012679784","display_name":"Haijun Du","orcid":"https://orcid.org/0000-0001-5425-5488"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Du, Huangsheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064523665","display_name":"Jingyang Meng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Meng, Jingyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139185404","display_name":"Ligang Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Ligang","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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.6787999868392944,"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":0.6787999868392944,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.14970000088214874,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.11029999703168869,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/focus","display_name":"Focus (optics)","score":0.5394999980926514},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.5182999968528748},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5108000040054321},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4514999985694885},{"id":"https://openalex.org/keywords/importance-sampling","display_name":"Importance sampling","score":0.3984000086784363},{"id":"https://openalex.org/keywords/global-illumination","display_name":"Global illumination","score":0.3804999887943268},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.37540000677108765},{"id":"https://openalex.org/keywords/adaptive-sampling","display_name":"Adaptive sampling","score":0.3474000096321106}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7700999975204468},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6013000011444092},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5764999985694885},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5394999980926514},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.5182999968528748},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5108000040054321},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4514999985694885},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.3984000086784363},{"id":"https://openalex.org/C89720835","wikidata":"https://www.wikidata.org/wiki/Q1531701","display_name":"Global illumination","level":3,"score":0.3804999887943268},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.37540000677108765},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.37070000171661377},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.367000013589859},{"id":"https://openalex.org/C2781395549","wikidata":"https://www.wikidata.org/wiki/Q4680762","display_name":"Adaptive sampling","level":3,"score":0.3474000096321106},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.34209999442100525},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.31769999861717224},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2840000092983246},{"id":"https://openalex.org/C116921373","wikidata":"https://www.wikidata.org/wiki/Q2816483","display_name":"Real-time rendering","level":3,"score":0.28279998898506165},{"id":"https://openalex.org/C44185422","wikidata":"https://www.wikidata.org/wiki/Q6002064","display_name":"Image-based modeling and rendering","level":3,"score":0.2786000072956085},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.26750001311302185},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.2637999951839447},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.26030001044273376}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.21898","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.21898","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.2606.21898","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.21898","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":0.5029613971710205,"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":{"3D":[0,13,54,114],"Gaussian":[1],"Splatting":[2],"(3DGS)":[3],"has":[4,41],"emerged":[5],"as":[6],"a":[7,37,61,92,119,134],"promising":[8],"method":[9,148],"for":[10,84,127,156],"high-quality,":[11],"real-time":[12,158],"reconstruction.":[14],"To":[15],"associate":[16],"3DGS":[17,40,64,71,96,121],"with":[18,124],"mesh":[19,38,74],"representations,":[20],"existing":[21],"methods":[22],"primarily":[23],"focus":[24],"on":[25,49,77],"3DGS-to-mesh":[26],"reconstruction":[27],"from":[28,73],"multi-view":[29],"images.":[30],"In":[31],"contrast,":[32],"the":[33,57,102,107,111],"problem":[34],"of":[35,47,106,113],"converting":[36],"into":[39],"received":[42],"comparatively":[43],"less":[44],"attention.":[45],"Instead":[46],"relying":[48],"heuristic":[50],"strategies":[51],"that":[52,99,146],"bind":[53],"Gaussians":[55],"to":[56,139],"mesh,":[58],"we":[59,90,117,132],"propose":[60,91,118],"novel":[62,120],"white-box":[63],"construction":[65,97],"framework,":[66],"termed":[67],"Mesh2GS,":[68],"which":[69],"generates":[70],"directly":[72],"geometry":[75],"based":[76],"plenoptic":[78,93],"sampling":[79,94,104],"theory,":[80],"achieving":[81],"Nyquist-level":[82],"performance":[83],"high-quality":[85],"global":[86],"illumination":[87,136],"rendering.":[88],"Firstly,":[89],"guided":[95],"strategy":[98],"theoretically":[100],"derives":[101],"minimum":[103],"rate":[105],"sampled":[108],"views":[109],"and":[110,152,161],"distribution":[112],"Gaussians.":[115],"Second,":[116],"update":[122],"procedure":[123],"albedo--shading":[125],"decomposition":[126],"efficient":[128],"global-illumination":[129],"capture.":[130],"Finally,":[131],"introduce":[133],"neural":[135],"enhancement":[137],"module":[138],"handle":[140],"non-Lambertian":[141,162],"effects.":[142],"Experimental":[143],"results":[144],"demonstrate":[145],"our":[147],"surpasses":[149],"state-of-the-art":[150],"baselines":[151],"is":[153],"practically":[154],"effective":[155],"both":[157],"shared":[159],"rendering":[160],"effects":[163],"capturing":[164],"specular":[165],"highlights.":[166],"The":[167],"project":[168],"code":[169],"will":[170],"be":[171],"released":[172],"upon":[173],"acceptance.":[174]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-24T00:00:00"}