{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:7JTEB5E3RBSWZ5GDYZSTN7QGPE","short_pith_number":"pith:7JTEB5E3","canonical_record":{"source":{"id":"2104.10369","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-04-21T06:13:29Z","cross_cats_sorted":["cs.GR"],"title_canon_sha256":"f6f9dacae02148d0e9aa3e08858ea3827d91f554fec50b2e69c1a36ebb0777fc","abstract_canon_sha256":"09abf25f49050690784892f36a647ac4df4dcba0784c45ca8bfba208f2b63ca1"},"schema_version":"1.0"},"canonical_sha256":"fa6640f49b88656cf4c3c66536fe06793ec8c8d611c394d35bd2845d50ae7c12","source":{"kind":"arxiv","id":"2104.10369","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.10369","created_at":"2026-07-05T02:34:01Z"},{"alias_kind":"arxiv_version","alias_value":"2104.10369v1","created_at":"2026-07-05T02:34:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.10369","created_at":"2026-07-05T02:34:01Z"},{"alias_kind":"pith_short_12","alias_value":"7JTEB5E3RBSW","created_at":"2026-07-05T02:34:01Z"},{"alias_kind":"pith_short_16","alias_value":"7JTEB5E3RBSWZ5GD","created_at":"2026-07-05T02:34:01Z"},{"alias_kind":"pith_short_8","alias_value":"7JTEB5E3","created_at":"2026-07-05T02:34:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:7JTEB5E3RBSWZ5GDYZSTN7QGPE","target":"record","payload":{"canonical_record":{"source":{"id":"2104.10369","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-04-21T06:13:29Z","cross_cats_sorted":["cs.GR"],"title_canon_sha256":"f6f9dacae02148d0e9aa3e08858ea3827d91f554fec50b2e69c1a36ebb0777fc","abstract_canon_sha256":"09abf25f49050690784892f36a647ac4df4dcba0784c45ca8bfba208f2b63ca1"},"schema_version":"1.0"},"canonical_sha256":"fa6640f49b88656cf4c3c66536fe06793ec8c8d611c394d35bd2845d50ae7c12","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:34:01.644573Z","signature_b64":"bNeHYNFXAnsSJ7mvKNt2V2Pb65hLOhPg+qYzNbbOqWk8Pph2RXSyL71VAvIBFTpc++ste1RdreqxVYE8GfPMDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fa6640f49b88656cf4c3c66536fe06793ec8c8d611c394d35bd2845d50ae7c12","last_reissued_at":"2026-07-05T02:34:01.644186Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:34:01.644186Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2104.10369","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:34:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nfpKrOcUzLa+M0B7jLj8edXZWHYeKxOfns6RdIdx3pvbKZUj/i3cDTKN8XVlyDIUtTp6jM38cEx4WEK0mV1ABg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T05:49:35.539659Z"},"content_sha256":"338d97410494939aa77373eebf25eaa1bc822330ef7871c18a2ff0e7d0d069a2","schema_version":"1.0","event_id":"sha256:338d97410494939aa77373eebf25eaa1bc822330ef7871c18a2ff0e7d0d069a2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:7JTEB5E3RBSWZ5GDYZSTN7QGPE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Improvement of Normal Estimation for PointClouds via Simplifying Surface Fitting","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.GR"],"primary_cat":"cs.CV","authors_text":"Jun Zhou, Mingjie Wang, Wei Jin, Xiuping Liu, Zhaobin Liu, Zhiyang Li","submitted_at":"2021-04-21T06:13:29Z","abstract_excerpt":"With the burst development of neural networks in recent years, the task of normal estimation has once again become a concern. By introducing the neural networks to classic methods based on problem-specific knowledge, the adaptability of the normal estimation algorithm to noise and scale has been greatly improved. However, the compatibility between neural networks and the traditional methods has not been considered. Similar to the principle of Occam's razor, that is, the simpler is better. We observe that a more simplified process of surface fitting can significantly improve the accuracy of the"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.10369","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/2104.10369/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:34:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RsO00ML4PDw0P1Qb2WaW9M3seS0L3ji9AWfuU54FwsSFdSxa/5qWhBOmm9ofvoWMbC3rfCd6DvhA70UCoHnLBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T05:49:35.540028Z"},"content_sha256":"139a9f70640a5893a4ef7f1be0f052f862e6da89bf109ebe3e66a1ed27ecf094","schema_version":"1.0","event_id":"sha256:139a9f70640a5893a4ef7f1be0f052f862e6da89bf109ebe3e66a1ed27ecf094"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7JTEB5E3RBSWZ5GDYZSTN7QGPE/bundle.json","state_url":"https://pith.science/pith/7JTEB5E3RBSWZ5GDYZSTN7QGPE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7JTEB5E3RBSWZ5GDYZSTN7QGPE/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-04T05:49:35Z","links":{"resolver":"https://pith.science/pith/7JTEB5E3RBSWZ5GDYZSTN7QGPE","bundle":"https://pith.science/pith/7JTEB5E3RBSWZ5GDYZSTN7QGPE/bundle.json","state":"https://pith.science/pith/7JTEB5E3RBSWZ5GDYZSTN7QGPE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7JTEB5E3RBSWZ5GDYZSTN7QGPE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:7JTEB5E3RBSWZ5GDYZSTN7QGPE","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"09abf25f49050690784892f36a647ac4df4dcba0784c45ca8bfba208f2b63ca1","cross_cats_sorted":["cs.GR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-04-21T06:13:29Z","title_canon_sha256":"f6f9dacae02148d0e9aa3e08858ea3827d91f554fec50b2e69c1a36ebb0777fc"},"schema_version":"1.0","source":{"id":"2104.10369","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.10369","created_at":"2026-07-05T02:34:01Z"},{"alias_kind":"arxiv_version","alias_value":"2104.10369v1","created_at":"2026-07-05T02:34:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.10369","created_at":"2026-07-05T02:34:01Z"},{"alias_kind":"pith_short_12","alias_value":"7JTEB5E3RBSW","created_at":"2026-07-05T02:34:01Z"},{"alias_kind":"pith_short_16","alias_value":"7JTEB5E3RBSWZ5GD","created_at":"2026-07-05T02:34:01Z"},{"alias_kind":"pith_short_8","alias_value":"7JTEB5E3","created_at":"2026-07-05T02:34:01Z"}],"graph_snapshots":[{"event_id":"sha256:139a9f70640a5893a4ef7f1be0f052f862e6da89bf109ebe3e66a1ed27ecf094","target":"graph","created_at":"2026-07-05T02:34:01Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2104.10369/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"With the burst development of neural networks in recent years, the task of normal estimation has once again become a concern. By introducing the neural networks to classic methods based on problem-specific knowledge, the adaptability of the normal estimation algorithm to noise and scale has been greatly improved. However, the compatibility between neural networks and the traditional methods has not been considered. Similar to the principle of Occam's razor, that is, the simpler is better. We observe that a more simplified process of surface fitting can significantly improve the accuracy of the","authors_text":"Jun Zhou, Mingjie Wang, Wei Jin, Xiuping Liu, Zhaobin Liu, Zhiyang Li","cross_cats":["cs.GR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-04-21T06:13:29Z","title":"Improvement of Normal Estimation for PointClouds via Simplifying Surface Fitting"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.10369","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:338d97410494939aa77373eebf25eaa1bc822330ef7871c18a2ff0e7d0d069a2","target":"record","created_at":"2026-07-05T02:34:01Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"09abf25f49050690784892f36a647ac4df4dcba0784c45ca8bfba208f2b63ca1","cross_cats_sorted":["cs.GR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-04-21T06:13:29Z","title_canon_sha256":"f6f9dacae02148d0e9aa3e08858ea3827d91f554fec50b2e69c1a36ebb0777fc"},"schema_version":"1.0","source":{"id":"2104.10369","kind":"arxiv","version":1}},"canonical_sha256":"fa6640f49b88656cf4c3c66536fe06793ec8c8d611c394d35bd2845d50ae7c12","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fa6640f49b88656cf4c3c66536fe06793ec8c8d611c394d35bd2845d50ae7c12","first_computed_at":"2026-07-05T02:34:01.644186Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:34:01.644186Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bNeHYNFXAnsSJ7mvKNt2V2Pb65hLOhPg+qYzNbbOqWk8Pph2RXSyL71VAvIBFTpc++ste1RdreqxVYE8GfPMDA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:34:01.644573Z","signed_message":"canonical_sha256_bytes"},"source_id":"2104.10369","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:338d97410494939aa77373eebf25eaa1bc822330ef7871c18a2ff0e7d0d069a2","sha256:139a9f70640a5893a4ef7f1be0f052f862e6da89bf109ebe3e66a1ed27ecf094"],"state_sha256":"87a6a3a65e0ea7ed9ab660b720000f58e3d1f78ac9723d313dfc0103afcbda68"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9aKGZNmECsnQ+iObNp/W6F+M0sGpLo+0GkGUZRZRUcQ/6IT610b1xFM/PkucIBK2U6+KTqCnn31eIwVmd6dFCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T05:49:35.542321Z","bundle_sha256":"247d40d24bcb4a2dc8dd6b54c2c162d87ece3886469fe3c92941b95f85a6fc8c"}}