{"id":"https://openalex.org/W4417124658","doi":"https://doi.org/10.1145/3757377.3763907","title":"Spectral-GS: Taming 3D Gaussian Splatting with Spectral Entropy","display_name":"Spectral-GS: Taming 3D Gaussian Splatting with Spectral Entropy","publication_year":2025,"publication_date":"2025-12-08","ids":{"openalex":"https://openalex.org/W4417124658","doi":"https://doi.org/10.1145/3757377.3763907"},"language":null,"primary_location":{"id":"doi:10.1145/3757377.3763907","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3757377.3763907","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the SIGGRAPH Asia 2025 Conference Papers","raw_type":"proceedings-article"},"type":"conference-paper","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/A5040718949","display_name":"L. Q. Huang","orcid":"https://orcid.org/0009-0003-1454-7824"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Letian Huang","raw_affiliation_strings":["State Key Lab for Novel Software Technology, Nanjing University, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0003-1454-7824","affiliations":[{"raw_affiliation_string":"State Key Lab for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042385843","display_name":"Jie Guo","orcid":"https://orcid.org/0000-0002-4176-7617"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Guo","raw_affiliation_strings":["State Key Lab for Novel Software Technology, Nanjing University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-4176-7617","affiliations":[{"raw_affiliation_string":"State Key Lab for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114400396","display_name":"Jialin Dan","orcid":"https://orcid.org/0009-0007-2228-4648"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jialin Dan","raw_affiliation_strings":["State Key Lab for Novel Software Technology, Nanjing University, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0007-2228-4648","affiliations":[{"raw_affiliation_string":"State Key Lab for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077629033","display_name":"Ruoyu Fu","orcid":"https://orcid.org/0009-0008-0557-4384"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruoyu Fu","raw_affiliation_strings":["State Key Lab for Novel Software Technology, Nanjing University, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0008-0557-4384","affiliations":[{"raw_affiliation_string":"State Key Lab for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022640746","display_name":"Yuanqi Li","orcid":"https://orcid.org/0000-0003-4100-7471"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanqi Li","raw_affiliation_strings":["State Key Lab for Novel Software Technology, Nanjing University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0003-4100-7471","affiliations":[{"raw_affiliation_string":"State Key Lab for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009275869","display_name":"Yanwen Guo","orcid":"https://orcid.org/0000-0002-7605-5206"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanwen Guo","raw_affiliation_strings":["State Key Lab for Novel Software Technology, Nanjing University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-7605-5206","affiliations":[{"raw_affiliation_string":"State Key Lab for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I881766915"],"apc_list":null,"apc_paid":null,"fwci":2.5375,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.92086721,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.5879999995231628,"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":0.5879999995231628,"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":0.17579999566078186,"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":0.054099999368190765,"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/smoothing","display_name":"Smoothing","score":0.6331999897956848},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5708000063896179},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5616000294685364},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.5004000067710876},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.42739999294281006},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.41449999809265137},{"id":"https://openalex.org/keywords/spectral-shape-analysis","display_name":"Spectral shape analysis","score":0.4115000069141388},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.38449999690055847},{"id":"https://openalex.org/keywords/zoom","display_name":"Zoom","score":0.3831999897956848}],"concepts":[{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.6331999897956848},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6025999784469604},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5708000063896179},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5616000294685364},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5568000078201294},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.5004000067710876},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.42739999294281006},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.41449999809265137},{"id":"https://openalex.org/C152822103","wikidata":"https://www.wikidata.org/wiki/Q7575207","display_name":"Spectral shape analysis","level":3,"score":0.4115000069141388},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4097999930381775},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.38449999690055847},{"id":"https://openalex.org/C124913957","wikidata":"https://www.wikidata.org/wiki/Q1232548","display_name":"Zoom","level":3,"score":0.3831999897956848},{"id":"https://openalex.org/C89735579","wikidata":"https://www.wikidata.org/wiki/Q6795894","display_name":"Maximum entropy spectral estimation","level":3,"score":0.3781000077724457},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.37619999051094055},{"id":"https://openalex.org/C65892221","wikidata":"https://www.wikidata.org/wiki/Q1113935","display_name":"Gaussian filter","level":3,"score":0.3752000033855438},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36910000443458557},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32839998602867126},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.32429999113082886},{"id":"https://openalex.org/C166963901","wikidata":"https://www.wikidata.org/wiki/Q287251","display_name":"Kurtosis","level":2,"score":0.3131999969482422},{"id":"https://openalex.org/C168110828","wikidata":"https://www.wikidata.org/wiki/Q1331626","display_name":"Spectral density","level":2,"score":0.2989000082015991},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.2969000041484833},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.2892000079154968},{"id":"https://openalex.org/C5806529","wikidata":"https://www.wikidata.org/wiki/Q2365325","display_name":"Orthonormal basis","level":2,"score":0.2800000011920929},{"id":"https://openalex.org/C174576160","wikidata":"https://www.wikidata.org/wiki/Q1183700","display_name":"Deconvolution","level":2,"score":0.27300000190734863},{"id":"https://openalex.org/C176641082","wikidata":"https://www.wikidata.org/wiki/Q2446767","display_name":"Spectral signature","level":2,"score":0.27300000190734863},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2727999985218048},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.2671000063419342},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.2621999979019165},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.2596000134944916},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.25949999690055847},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3757377.3763907","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3757377.3763907","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the SIGGRAPH Asia 2025 Conference Papers","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2342739902","display_name":"\u53cc\u5411\u53cd\u5c04\u5206\u5e03\u51fd\u6570\u7684\u7403\u9762\u7edf\u8ba1\u5206\u6790\u53ca\u5176\u667a\u80fd\u5316\u5e94\u7528\u7814\u7a76","funder_award_id":"61972194","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7764877933","display_name":null,"funder_award_id":"BK20211147","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W320879671","https://openalex.org/W1885185971","https://openalex.org/W1995875735","https://openalex.org/W2294343556","https://openalex.org/W2738551266","https://openalex.org/W2901982540","https://openalex.org/W2962785568","https://openalex.org/W3109585842","https://openalex.org/W3203570626","https://openalex.org/W3215769467","https://openalex.org/W4221151978","https://openalex.org/W4312679369","https://openalex.org/W4385318467","https://openalex.org/W4390872696","https://openalex.org/W4390873066","https://openalex.org/W4391506026","https://openalex.org/W4391800855","https://openalex.org/W4396786944","https://openalex.org/W4400403028","https://openalex.org/W4402716153","https://openalex.org/W4402716301","https://openalex.org/W4403843633","https://openalex.org/W4404965464","https://openalex.org/W4404978047","https://openalex.org/W4407127931","https://openalex.org/W4409334625","https://openalex.org/W4410617762","https://openalex.org/W4412673715","https://openalex.org/W4415796646"],"related_works":[],"abstract_inverted_index":{"Recently,":[0],"3D":[1,38,154],"Gaussian":[2],"Splatting":[3],"(3DGS)":[4],"has":[5],"achieved":[6],"impressive":[7],"results":[8],"in":[9,120,135],"novel":[10,138],"view":[11,89,141],"synthesis,":[12],"demonstrating":[13],"high":[14],"fidelity":[15],"and":[16,44,59,74,88,104,111,122,128,143,157,176],"efficiency.":[17],"However,":[18],"it":[19,53],"easily":[20],"exhibits":[21],"needle-like":[22,61,98],"artifacts,":[23,175],"especially":[24],"when":[25],"increasing":[26],"the":[27,69,117,125,130],"sampling":[28],"rate.":[29],"Mip-Splatting":[30,123],"tries":[31],"to":[32,55,92,109,136,169],"remove":[33],"these":[34,164],"artifacts":[35],"with":[36,100],"a":[37,45,96],"smoothing":[39],"filter":[40,48],"for":[41,49],"frequency":[42],"constraints":[43],"2D":[46,158],"Mip":[47],"approximated":[50],"supersampling.":[51],"Unfortunately,":[52],"tends":[54],"produce":[56],"over-blurred":[57],"results,":[58],"sometimes":[60],"Gaussians":[62,99],"still":[63],"persist.":[64],"Our":[65,147],"spectral":[66,86,106,126,151],"analysis":[67],"of":[68],"covariance":[70],"matrix":[71],"during":[72,133],"optimization":[73],"densification":[75],"reveals":[76],"that":[77],"current":[78],"3DGS":[79,121],"lacks":[80],"shape":[81],"awareness,":[82],"relying":[83],"instead":[84],"on":[85,150],"radius":[87],"positional":[90,102],"gradients":[91,103],"determine":[93],"splitting.":[94],"As":[95],"result,":[97],"small":[101],"low":[105],"entropy":[107,127],"fail":[108],"split":[110],"overfit":[112],"high-frequency":[113,171],"details.":[114],"Furthermore,":[115],"both":[116],"filters":[118],"used":[119],"reduce":[124],"increase":[129],"condition":[131],"number":[132],"zooming":[134],"synthesize":[137],"view,":[139],"causing":[140],"inconsistencies":[142],"more":[144],"pronounced":[145],"artifacts.":[146],"Spectral-GS,":[148],"based":[149],"analysis,":[152],"introduces":[153],"shape-aware":[155],"splitting":[156],"view-consistent":[159],"filtering":[160],"strategies,":[161],"effectively":[162],"addressing":[163],"issues,":[165],"enhancing":[166],"3DGS\u2019s":[167],"capability":[168],"represent":[170],"details":[172],"without":[173],"noticeable":[174],"achieving":[177],"high-quality":[178],"realistic":[179],"rendering.":[180]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-08-06T08:24:18.245995","created_date":"2025-12-08T00:00:00"}
