{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:YWUC2NN2GYNG3QZXGCONPIJBI6","short_pith_number":"pith:YWUC2NN2","schema_version":"1.0","canonical_sha256":"c5a82d35ba361a6dc337309cd7a12147b99b6813e66d5a19653f5d3d1d847053","source":{"kind":"arxiv","id":"2503.13541","version":1},"attestation_state":"computed","paper":{"title":"DDPM-Polycube: A Denoising Diffusion Probabilistic Model for Polycube-Based Hexahedral Mesh Generation and Volumetric Spline Construction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.GR","authors_text":"Hua Tong, Jiashuo Liu, Yongjie Jessica Zhang, Yuxuan Yu, Yuzhuo Fang","submitted_at":"2025-03-16T04:29:40Z","abstract_excerpt":"In this paper, we propose DDPM-Polycube, a generative polycube creation approach based on denoising diffusion probabilistic models (DDPM) for generating high-quality hexahedral (hex) meshes and constructing volumetric splines. Unlike DL-Polycube methods that rely on predefined polycube structure templates, DDPM-Polycube models the deformation from input geometry to its corresponding polycube structures as a denoising task. By learning the deformation characteristics of simple geometric primitives (a cube and a cube with a hole), the DDPM-Polycube model progressively reconstructs polycube struc"},"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":"2503.13541","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GR","submitted_at":"2025-03-16T04:29:40Z","cross_cats_sorted":[],"title_canon_sha256":"dc571f2427570ab181dcffc2a08a6ef7d79000c0dd73c8add2e1a977784bd9b3","abstract_canon_sha256":"3e267d89f6ae75a96ebf7a8893615db46f15375ce646cb90f280882f900d5b86"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:33:12.422112Z","signature_b64":"ps16Y74nPXuB5DJLN/5ez7fWAMlgO2P6psV0aGYPPp7/K3bPoquYeGEZOn2DwFORoeb/S1xD4ZPyS789p4/qDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c5a82d35ba361a6dc337309cd7a12147b99b6813e66d5a19653f5d3d1d847053","last_reissued_at":"2026-07-05T10:33:12.421625Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:33:12.421625Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"DDPM-Polycube: A Denoising Diffusion Probabilistic Model for Polycube-Based Hexahedral Mesh Generation and Volumetric Spline Construction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.GR","authors_text":"Hua Tong, Jiashuo Liu, Yongjie Jessica Zhang, Yuxuan Yu, Yuzhuo Fang","submitted_at":"2025-03-16T04:29:40Z","abstract_excerpt":"In this paper, we propose DDPM-Polycube, a generative polycube creation approach based on denoising diffusion probabilistic models (DDPM) for generating high-quality hexahedral (hex) meshes and constructing volumetric splines. Unlike DL-Polycube methods that rely on predefined polycube structure templates, DDPM-Polycube models the deformation from input geometry to its corresponding polycube structures as a denoising task. By learning the deformation characteristics of simple geometric primitives (a cube and a cube with a hole), the DDPM-Polycube model progressively reconstructs polycube struc"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.13541","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/2503.13541/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":"2503.13541","created_at":"2026-07-05T10:33:12.421683+00:00"},{"alias_kind":"arxiv_version","alias_value":"2503.13541v1","created_at":"2026-07-05T10:33:12.421683+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.13541","created_at":"2026-07-05T10:33:12.421683+00:00"},{"alias_kind":"pith_short_12","alias_value":"YWUC2NN2GYNG","created_at":"2026-07-05T10:33:12.421683+00:00"},{"alias_kind":"pith_short_16","alias_value":"YWUC2NN2GYNG3QZX","created_at":"2026-07-05T10:33:12.421683+00:00"},{"alias_kind":"pith_short_8","alias_value":"YWUC2NN2","created_at":"2026-07-05T10:33:12.421683+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/YWUC2NN2GYNG3QZXGCONPIJBI6","json":"https://pith.science/pith/YWUC2NN2GYNG3QZXGCONPIJBI6.json","graph_json":"https://pith.science/api/pith-number/YWUC2NN2GYNG3QZXGCONPIJBI6/graph.json","events_json":"https://pith.science/api/pith-number/YWUC2NN2GYNG3QZXGCONPIJBI6/events.json","paper":"https://pith.science/paper/YWUC2NN2"},"agent_actions":{"view_html":"https://pith.science/pith/YWUC2NN2GYNG3QZXGCONPIJBI6","download_json":"https://pith.science/pith/YWUC2NN2GYNG3QZXGCONPIJBI6.json","view_paper":"https://pith.science/paper/YWUC2NN2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2503.13541&json=true","fetch_graph":"https://pith.science/api/pith-number/YWUC2NN2GYNG3QZXGCONPIJBI6/graph.json","fetch_events":"https://pith.science/api/pith-number/YWUC2NN2GYNG3QZXGCONPIJBI6/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YWUC2NN2GYNG3QZXGCONPIJBI6/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YWUC2NN2GYNG3QZXGCONPIJBI6/action/storage_attestation","attest_author":"https://pith.science/pith/YWUC2NN2GYNG3QZXGCONPIJBI6/action/author_attestation","sign_citation":"https://pith.science/pith/YWUC2NN2GYNG3QZXGCONPIJBI6/action/citation_signature","submit_replication":"https://pith.science/pith/YWUC2NN2GYNG3QZXGCONPIJBI6/action/replication_record"}},"created_at":"2026-07-05T10:33:12.421683+00:00","updated_at":"2026-07-05T10:33:12.421683+00:00"}