{"id":"https://openalex.org/W7154737015","doi":"https://doi.org/10.48550/arxiv.2604.14928","title":"Hybrid Latents: Geometry-Appearance-Aware Surfel Splatting","display_name":"Hybrid Latents: Geometry-Appearance-Aware Surfel Splatting","publication_year":2026,"publication_date":"2026-04-16","ids":{"openalex":"https://openalex.org/W7154737015","doi":"https://doi.org/10.48550/arxiv.2604.14928"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.14928","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.14928","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.14928","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133868131","display_name":"Neel Kelkar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kelkar, Neel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093701028","display_name":"Simon Niedermayr","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Niedermayr, Simon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112479325","display_name":"Klaus Engel","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Engel, Klaus","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5029621326","display_name":"R\u00fcdiger Westermann","orcid":"https://orcid.org/0000-0002-3394-0731"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Westermann, R\u00fcdiger","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.4016000032424927,"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"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.4016000032424927,"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"}},{"id":"https://openalex.org/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.31869998574256897,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.12809999287128448,"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/rendering","display_name":"Rendering (computer graphics)","score":0.5444999933242798},{"id":"https://openalex.org/keywords/texture-synthesis","display_name":"Texture synthesis","score":0.5029000043869019},{"id":"https://openalex.org/keywords/view-synthesis","display_name":"View synthesis","score":0.4546000063419342},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.40950000286102295},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.39559999108314514},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.3953999876976013},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3700000047683716},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.3564000129699707},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.34200000762939453}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7127000093460083},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6128000020980835},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5699999928474426},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.5444999933242798},{"id":"https://openalex.org/C50494287","wikidata":"https://www.wikidata.org/wiki/Q658467","display_name":"Texture synthesis","level":5,"score":0.5029000043869019},{"id":"https://openalex.org/C2776449333","wikidata":"https://www.wikidata.org/wiki/Q7928781","display_name":"View synthesis","level":3,"score":0.4546000063419342},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41119998693466187},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.40950000286102295},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.39559999108314514},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3953999876976013},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3700000047683716},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.3564000129699707},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.35249999165534973},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.34200000762939453},{"id":"https://openalex.org/C60056205","wikidata":"https://www.wikidata.org/wiki/Q691914","display_name":"Opacity","level":2,"score":0.32820001244544983},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.325300008058548},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.3176000118255615},{"id":"https://openalex.org/C89720835","wikidata":"https://www.wikidata.org/wiki/Q1531701","display_name":"Global illumination","level":3,"score":0.3149999976158142},{"id":"https://openalex.org/C83248878","wikidata":"https://www.wikidata.org/wiki/Q344000","display_name":"Active appearance model","level":3,"score":0.3100000023841858},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.3075999915599823},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.3050999939441681},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.29010000824928284},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.27900001406669617},{"id":"https://openalex.org/C23690007","wikidata":"https://www.wikidata.org/wiki/Q1411145","display_name":"Radiance","level":2,"score":0.27630001306533813},{"id":"https://openalex.org/C200585589","wikidata":"https://www.wikidata.org/wiki/Q752176","display_name":"Texture mapping","level":2,"score":0.26669999957084656},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.2635999917984009},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.258899986743927},{"id":"https://openalex.org/C44185422","wikidata":"https://www.wikidata.org/wiki/Q6002064","display_name":"Image-based modeling and rendering","level":3,"score":0.25589999556541443}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.14928","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.14928","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.14928","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.14928","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":"article"},"sustainable_development_goals":[{"score":0.7347338795661926,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0],"introduce":[1],"a":[2,46,95,108],"hybrid":[3],"Gaussian-hash-grid":[4],"radiance":[5],"representation":[6],"for":[7,66],"reconstructing":[8],"2D":[9],"Gaussian":[10],"scene":[11,52],"models":[12],"from":[13],"multi-view":[14],"images.":[15],"Similar":[16],"to":[17,41,64,103,114],"NeST":[18],"splatting,":[19],"our":[20],"approach":[21],"reduces":[22,58],"the":[23,43,59,77,116,127,130],"entanglement":[24],"between":[25,79],"geometry":[26,80,85],"and":[27,50,81,87,121,136],"appearance":[28],"common":[29],"in":[30,132],"NeRF-based":[31],"models,":[32],"but":[33],"adds":[34],"per-Gaussian":[35],"latent":[36],"features":[37,40],"alongside":[38],"hash-grid":[39],"bias":[42],"optimizer":[44],"toward":[45],"separation":[47,78],"of":[48,61,111,129,144],"low-":[49],"high-frequency":[51,62],"components.":[53],"This":[54],"explicit":[55],"frequency-based":[56],"decomposition":[57],"tendency":[60],"texture":[63],"compensate":[65],"geometric":[67],"errors.":[68],"Encouraging":[69],"Gaussians":[70,102,112],"with":[71,94,141],"hard":[72],"opacity":[73,98],"falloffs":[74],"further":[75],"strengthens":[76],"appearance,":[82],"improving":[83],"both":[84,119],"reconstruction":[86,139],"rendering":[88],"efficiency.":[89],"Finally,":[90],"probabilistic":[91],"pruning":[92],"combined":[93],"sparsity-inducing":[96],"BCE":[97],"loss":[99],"allows":[100],"redundant":[101],"be":[104],"turned":[105],"off,":[106],"yielding":[107],"minimal":[109],"set":[110],"sufficient":[113],"represent":[115],"scene.":[117],"Using":[118],"synthetic":[120],"real-world":[122],"datasets,":[123],"we":[124],"compare":[125],"against":[126],"state":[128],"art":[131],"Gaussian-based":[133],"novel-view":[134],"synthesis":[135],"demonstrate":[137],"superior":[138],"fidelity":[140],"an":[142],"order":[143],"magnitude":[145],"fewer":[146],"primitives.":[147]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-18T00:00:00"}
