{"id":"https://openalex.org/W7164051538","doi":"https://doi.org/10.48550/arxiv.2606.08469","title":"OctaOctree Neural Radiosity for Real-time Glossy Material Rendering","display_name":"OctaOctree Neural Radiosity for Real-time Glossy Material Rendering","publication_year":2026,"publication_date":"2026-06-07","ids":{"openalex":"https://openalex.org/W7164051538","doi":"https://doi.org/10.48550/arxiv.2606.08469"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.08469","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.08469","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.2606.08469","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008235393","display_name":"Jierui Ren","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ren, Jierui","raw_affiliation_strings":["Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135692888","display_name":"Haojie Jin","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin, Haojie","raw_affiliation_strings":["Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114196302","display_name":"Bo Pang","orcid":"https://orcid.org/0009-0007-3189-8430"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pang, Bo","raw_affiliation_strings":["Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055461368","display_name":"Meng Gai","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gai, Meng","raw_affiliation_strings":["Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100863053","display_name":"Fei Zhu","orcid":"https://orcid.org/0009-0002-3564-460X"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhu, Fei","raw_affiliation_strings":["Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101508336","display_name":"Yuehua Chen","orcid":"https://orcid.org/0000-0002-4646-4017"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen, Yisong","raw_affiliation_strings":["Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5138241666","display_name":"Sheng Li","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li, Sheng","raw_affiliation_strings":["Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I20231570"],"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":0.9483000040054321,"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":0.9483000040054321,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.014600000344216824,"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/T11666","display_name":"Color Science and Applications","score":0.003700000001117587,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/radiance","display_name":"Radiance","score":0.9642000198364258},{"id":"https://openalex.org/keywords/global-illumination","display_name":"Global illumination","score":0.7573000192642212},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.6395999789237976},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4855000078678131},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.42260000109672546},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4162999987602234},{"id":"https://openalex.org/keywords/radiosity","display_name":"Radiosity (computer graphics)","score":0.39899998903274536},{"id":"https://openalex.org/keywords/ray-tracing","display_name":"Ray tracing (physics)","score":0.37860000133514404}],"concepts":[{"id":"https://openalex.org/C23690007","wikidata":"https://www.wikidata.org/wiki/Q1411145","display_name":"Radiance","level":2,"score":0.9642000198364258},{"id":"https://openalex.org/C89720835","wikidata":"https://www.wikidata.org/wiki/Q1531701","display_name":"Global illumination","level":3,"score":0.7573000192642212},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7444000244140625},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.6395999789237976},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5428000092506409},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5364000201225281},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4855000078678131},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.42260000109672546},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4162999987602234},{"id":"https://openalex.org/C146168522","wikidata":"https://www.wikidata.org/wiki/Q1068239","display_name":"Radiosity (computer graphics)","level":2,"score":0.39899998903274536},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3855000138282776},{"id":"https://openalex.org/C121483023","wikidata":"https://www.wikidata.org/wiki/Q7298343","display_name":"Ray tracing (physics)","level":2,"score":0.37860000133514404},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.37770000100135803},{"id":"https://openalex.org/C2778597888","wikidata":"https://www.wikidata.org/wiki/Q172169","display_name":"3D city models","level":3,"score":0.3693000078201294},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.36899998784065247},{"id":"https://openalex.org/C123403432","wikidata":"https://www.wikidata.org/wiki/Q654068","display_name":"Visibility","level":2,"score":0.3682999908924103},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.36340001225471497},{"id":"https://openalex.org/C110541219","wikidata":"https://www.wikidata.org/wiki/Q72948","display_name":"Path tracing","level":3,"score":0.34540000557899475},{"id":"https://openalex.org/C2780056265","wikidata":"https://www.wikidata.org/wiki/Q106239881","display_name":"High dynamic range","level":3,"score":0.3450999855995178},{"id":"https://openalex.org/C141297171","wikidata":"https://www.wikidata.org/wiki/Q1143237","display_name":"Octree","level":2,"score":0.33250001072883606},{"id":"https://openalex.org/C118381688","wikidata":"https://www.wikidata.org/wiki/Q1079524","display_name":"Specular reflection","level":2,"score":0.2937000095844269},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.28859999775886536},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.26260000467300415},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.26089999079704285},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.2506999969482422}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.08469","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.08469","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.2606.08469","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.08469","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Modeling":[0],"high-frequency":[1,146],"outgoing":[2,68],"radiance":[3,20,41,61,69,121,133,208],"distributions":[4],"remains":[5],"a":[6,126,154,158,165],"fundamental":[7],"challenge":[8],"in":[9,74],"global":[10,64,187],"illumination,":[11],"especially":[12],"for":[13,63,164],"glossy":[14,118,177],"and":[15,77,104,119,160,199,207],"specular":[16,120],"materials.":[17],"Existing":[18],"neural-based":[19],"caching":[21,209],"methods":[22],"commonly":[23],"rely":[24],"on":[25,138],"positional":[26,150],"feature":[27],"encodings":[28],"or":[29,48,141],"spatially":[30],"organized":[31],"caches,":[32],"which":[33],"makes":[34],"it":[35],"difficult":[36],"to":[37,101,116,144,175],"represent":[38],"sharp":[39,176],"directional":[40,85],"variations":[42],"without":[43],"increasing":[44],"the":[45,89,132,136],"model":[46],"complexity":[47],"sampling":[49],"cost.":[50],"To":[51],"address":[52],"this":[53],"challenge,":[54],"we":[55],"propose":[56],"OctaOctree,":[57],"an":[58,71,83],"efficient":[59],"spatial-angular":[60,128],"representation":[62,96],"illumination.":[65],"OctaOctree":[66,156],"organizes":[67],"with":[70,82,92,112,189,203],"adaptive":[72],"octree":[73],"3D":[75],"space,":[76],"associates":[78],"each":[79],"spatial":[80,90,99,110],"node":[81],"octahedral":[84],"map.":[86],"By":[87],"coupling":[88],"hierarchy":[91],"direction-dependent":[93],"storage,":[94],"our":[95,182],"allocates":[97],"fine":[98],"resolution":[100,115],"local":[102],"illumination":[103,170,188],"visibility":[105],"changes,":[106],"while":[107],"using":[108],"coarser":[109],"levels":[111],"richer":[113],"angular":[114],"capture":[117],"distributions.":[122],"This":[123],"design":[124],"embeds":[125],"reflectance-aware":[127],"prior":[129],"directly":[130],"into":[131],"representation,":[134],"reducing":[135],"burden":[137],"neural":[139,162,205],"networks":[140],"reconstruction":[142],"modules":[143],"recover":[145],"view-dependent":[147],"effects":[148],"from":[149,172],"features":[151],"alone.":[152],"As":[153],"result,":[155],"provides":[157],"compact":[159],"expressive":[161],"encoding":[163],"wide":[166],"range":[167],"of":[168],"indirect":[169],"effects,":[171],"diffuse":[173],"interreflection":[174],"reflections.":[178],"Experiments":[179],"demonstrate":[180],"that":[181],"method":[183],"produces":[184],"high-quality,":[185],"direction-aware":[186],"single":[190],"network":[191],"query":[192],"at":[193],"primary":[194],"intersections,":[195],"achieving":[196],"improved":[197],"fidelity":[198],"real-time":[200],"performance":[201],"compared":[202],"baseline":[204],"radiosity":[206],"approaches.":[210]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-10T00:00:00"}
