{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:4A4BSABVI4VQWEMZR3DXZMAOQM","short_pith_number":"pith:4A4BSABV","schema_version":"1.0","canonical_sha256":"e038190035472b0b11998ec77cb00e832579df9da5a3ad048b64a24508ee65fd","source":{"kind":"arxiv","id":"2607.27943","version":1},"attestation_state":"computed","paper":{"title":"Compact Representation of Mipmapped SVBRDFs via Shared Gaussians","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.GR","authors_text":"Fengdi Zhang, Haocheng Ren, Hongwei Li, Jibing Lou, qing Luo, Yaqing Li","submitted_at":"2026-07-30T09:51:18Z","abstract_excerpt":"Spatially-varying BRDFs (SVBRDFs) are central to material representation in computer graphics, but their high-resolution, multi-channel, mipmapped textures impose a substantial storage burden. Existing compression methods face a fundamental trade-off: block-based compression provides random access and hardware-friendly decoding but exploits redundancy only within local blocks; image codecs offer strong rate-distortion performance but are not designed for direct real-time texture access; and neural texture compression achieves high compression ratios but requires neural inference during decodin"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2607.27943","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.GR","submitted_at":"2026-07-30T09:51:18Z","cross_cats_sorted":[],"title_canon_sha256":"3bf4129235a740a34449907904c41740f398e5ac3fcef403e8285e42a66262bc","abstract_canon_sha256":"00c63edd270e3b979ccc80ac82e4953b9fd61b0b79eb70aa878e03d8f55d9efc"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e038190035472b0b11998ec77cb00e832579df9da5a3ad048b64a24508ee65fd","last_reissued_at":"2026-07-31T01:34:51.652460Z","signature_status":"unsigned_v0","first_computed_at":"2026-07-31T01:34:51.652460Z"},"graph_snapshot":{"paper":{"title":"Compact Representation of Mipmapped SVBRDFs via Shared Gaussians","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.GR","authors_text":"Fengdi Zhang, Haocheng Ren, Hongwei Li, Jibing Lou, qing Luo, Yaqing Li","submitted_at":"2026-07-30T09:51:18Z","abstract_excerpt":"Spatially-varying BRDFs (SVBRDFs) are central to material representation in computer graphics, but their high-resolution, multi-channel, mipmapped textures impose a substantial storage burden. Existing compression methods face a fundamental trade-off: block-based compression provides random access and hardware-friendly decoding but exploits redundancy only within local blocks; image codecs offer strong rate-distortion performance but are not designed for direct real-time texture access; and neural texture compression achieves high compression ratios but requires neural inference during decodin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.27943","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2607.27943/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2607.27943","created_at":"2026-07-31T01:34:51.655590+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.27943v1","created_at":"2026-07-31T01:34:51.655590+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.27943","created_at":"2026-07-31T01:34:51.655590+00:00"},{"alias_kind":"pith_short_12","alias_value":"4A4BSABVI4VQ","created_at":"2026-07-31T01:34:51.655590+00:00"},{"alias_kind":"pith_short_16","alias_value":"4A4BSABVI4VQWEMZ","created_at":"2026-07-31T01:34:51.655590+00:00"},{"alias_kind":"pith_short_8","alias_value":"4A4BSABV","created_at":"2026-07-31T01:34:51.655590+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/4A4BSABVI4VQWEMZR3DXZMAOQM","json":"https://pith.science/pith/4A4BSABVI4VQWEMZR3DXZMAOQM.json","graph_json":"https://pith.science/api/pith-number/4A4BSABVI4VQWEMZR3DXZMAOQM/graph.json","events_json":"https://pith.science/api/pith-number/4A4BSABVI4VQWEMZR3DXZMAOQM/events.json","paper":"https://pith.science/paper/4A4BSABV"},"agent_actions":{"view_html":"https://pith.science/pith/4A4BSABVI4VQWEMZR3DXZMAOQM","download_json":"https://pith.science/pith/4A4BSABVI4VQWEMZR3DXZMAOQM.json","view_paper":"https://pith.science/paper/4A4BSABV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.27943&json=true","fetch_graph":"https://pith.science/api/pith-number/4A4BSABVI4VQWEMZR3DXZMAOQM/graph.json","fetch_events":"https://pith.science/api/pith-number/4A4BSABVI4VQWEMZR3DXZMAOQM/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/4A4BSABVI4VQWEMZR3DXZMAOQM/action/timestamp_anchor","attest_storage":"https://pith.science/pith/4A4BSABVI4VQWEMZR3DXZMAOQM/action/storage_attestation","attest_author":"https://pith.science/pith/4A4BSABVI4VQWEMZR3DXZMAOQM/action/author_attestation","sign_citation":"https://pith.science/pith/4A4BSABVI4VQWEMZR3DXZMAOQM/action/citation_signature","submit_replication":"https://pith.science/pith/4A4BSABVI4VQWEMZR3DXZMAOQM/action/replication_record"}},"created_at":"2026-07-31T01:34:51.655590+00:00","updated_at":"2026-07-31T01:34:51.655590+00:00"}