{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:K534FBYGIEPAL2EZDOBLFYMMGF","short_pith_number":"pith:K534FBYG","schema_version":"1.0","canonical_sha256":"5777c28706411e05e8991b82b2e18c315cfdf5a6cc65f4a7914a38dbc610e17c","source":{"kind":"arxiv","id":"2307.04013","version":2},"attestation_state":"computed","paper":{"title":"BPNet: B\\'ezier Primitive Segmentation on 3D Point Clouds","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Cheng Wen, Pierre Alliez, Qian Li, Rao Fu, Xiao Xiao","submitted_at":"2023-07-08T16:46:01Z","abstract_excerpt":"This paper proposes BPNet, a novel end-to-end deep learning framework to learn B\\'ezier primitive segmentation on 3D point clouds. The existing works treat different primitive types separately, thus limiting them to finite shape categories. To address this issue, we seek a generalized primitive segmentation on point clouds. Taking inspiration from B\\'ezier decomposition on NURBS models, we transfer it to guide point cloud segmentation casting off primitive types. A joint optimization framework is proposed to learn B\\'ezier primitive segmentation and geometric fitting simultaneously on a cascad"},"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":"2307.04013","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-07-08T16:46:01Z","cross_cats_sorted":[],"title_canon_sha256":"4624c53c79c18b0d2dc192100aa5ff29c84c61cdee75db205ebeb6325b82c1de","abstract_canon_sha256":"3a56e4f80c192b1f2271416000ae895814328b702ffa93b2a1f36ea57b0e1173"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:52:35.707784Z","signature_b64":"rDgKnB+7Pm2GWjrI3LvM+dCMSS071K78kKwQr+KoZp6HHxVg9b/ScF/IIDTP/LTklZ0AcOiPNHnNDMHFpE8wAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5777c28706411e05e8991b82b2e18c315cfdf5a6cc65f4a7914a38dbc610e17c","last_reissued_at":"2026-07-05T10:52:35.707327Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:52:35.707327Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"BPNet: B\\'ezier Primitive Segmentation on 3D Point Clouds","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Cheng Wen, Pierre Alliez, Qian Li, Rao Fu, Xiao Xiao","submitted_at":"2023-07-08T16:46:01Z","abstract_excerpt":"This paper proposes BPNet, a novel end-to-end deep learning framework to learn B\\'ezier primitive segmentation on 3D point clouds. The existing works treat different primitive types separately, thus limiting them to finite shape categories. To address this issue, we seek a generalized primitive segmentation on point clouds. Taking inspiration from B\\'ezier decomposition on NURBS models, we transfer it to guide point cloud segmentation casting off primitive types. A joint optimization framework is proposed to learn B\\'ezier primitive segmentation and geometric fitting simultaneously on a cascad"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.04013","kind":"arxiv","version":2},"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/2307.04013/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":"2307.04013","created_at":"2026-07-05T10:52:35.707387+00:00"},{"alias_kind":"arxiv_version","alias_value":"2307.04013v2","created_at":"2026-07-05T10:52:35.707387+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.04013","created_at":"2026-07-05T10:52:35.707387+00:00"},{"alias_kind":"pith_short_12","alias_value":"K534FBYGIEPA","created_at":"2026-07-05T10:52:35.707387+00:00"},{"alias_kind":"pith_short_16","alias_value":"K534FBYGIEPAL2EZ","created_at":"2026-07-05T10:52:35.707387+00:00"},{"alias_kind":"pith_short_8","alias_value":"K534FBYG","created_at":"2026-07-05T10:52:35.707387+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/K534FBYGIEPAL2EZDOBLFYMMGF","json":"https://pith.science/pith/K534FBYGIEPAL2EZDOBLFYMMGF.json","graph_json":"https://pith.science/api/pith-number/K534FBYGIEPAL2EZDOBLFYMMGF/graph.json","events_json":"https://pith.science/api/pith-number/K534FBYGIEPAL2EZDOBLFYMMGF/events.json","paper":"https://pith.science/paper/K534FBYG"},"agent_actions":{"view_html":"https://pith.science/pith/K534FBYGIEPAL2EZDOBLFYMMGF","download_json":"https://pith.science/pith/K534FBYGIEPAL2EZDOBLFYMMGF.json","view_paper":"https://pith.science/paper/K534FBYG","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2307.04013&json=true","fetch_graph":"https://pith.science/api/pith-number/K534FBYGIEPAL2EZDOBLFYMMGF/graph.json","fetch_events":"https://pith.science/api/pith-number/K534FBYGIEPAL2EZDOBLFYMMGF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/K534FBYGIEPAL2EZDOBLFYMMGF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/K534FBYGIEPAL2EZDOBLFYMMGF/action/storage_attestation","attest_author":"https://pith.science/pith/K534FBYGIEPAL2EZDOBLFYMMGF/action/author_attestation","sign_citation":"https://pith.science/pith/K534FBYGIEPAL2EZDOBLFYMMGF/action/citation_signature","submit_replication":"https://pith.science/pith/K534FBYGIEPAL2EZDOBLFYMMGF/action/replication_record"}},"created_at":"2026-07-05T10:52:35.707387+00:00","updated_at":"2026-07-05T10:52:35.707387+00:00"}