{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:SOWJ64GEQ7U6Q3JDXW2RN26YJB","short_pith_number":"pith:SOWJ64GE","canonical_record":{"source":{"id":"2104.09023","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-04-19T02:41:15Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"76be5c05f4679e0827172c0cc52031c8a94bed9a7461e0889d2e8d9c7f6757b0","abstract_canon_sha256":"72ae1f2b9344c36138c033162ff3d1f7bd6e53aefda80921b5067f3874628a7b"},"schema_version":"1.0"},"canonical_sha256":"93ac9f70c487e9e86d23bdb516ebd848687027e39ee51ff9ec74c40abda4b04e","source":{"kind":"arxiv","id":"2104.09023","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.09023","created_at":"2026-07-05T02:32:58Z"},{"alias_kind":"arxiv_version","alias_value":"2104.09023v1","created_at":"2026-07-05T02:32:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.09023","created_at":"2026-07-05T02:32:58Z"},{"alias_kind":"pith_short_12","alias_value":"SOWJ64GEQ7U6","created_at":"2026-07-05T02:32:58Z"},{"alias_kind":"pith_short_16","alias_value":"SOWJ64GEQ7U6Q3JD","created_at":"2026-07-05T02:32:58Z"},{"alias_kind":"pith_short_8","alias_value":"SOWJ64GE","created_at":"2026-07-05T02:32:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:SOWJ64GEQ7U6Q3JDXW2RN26YJB","target":"record","payload":{"canonical_record":{"source":{"id":"2104.09023","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-04-19T02:41:15Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"76be5c05f4679e0827172c0cc52031c8a94bed9a7461e0889d2e8d9c7f6757b0","abstract_canon_sha256":"72ae1f2b9344c36138c033162ff3d1f7bd6e53aefda80921b5067f3874628a7b"},"schema_version":"1.0"},"canonical_sha256":"93ac9f70c487e9e86d23bdb516ebd848687027e39ee51ff9ec74c40abda4b04e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:32:58.060697Z","signature_b64":"+bYINZ6sUcP2wK1XLnhAGZSEYmq2L9RV9GMYehnztg6SDpR8kbQrDebA1/zYY17/ncb4DTHl5jN8ZyoYFROoAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"93ac9f70c487e9e86d23bdb516ebd848687027e39ee51ff9ec74c40abda4b04e","last_reissued_at":"2026-07-05T02:32:58.060280Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:32:58.060280Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2104.09023","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":"2026-07-05T02:32:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2ti8uSkT2jcgTd3YHKVsi+q+v9Ty8om5ad7zf8ALTNVfSmx1YFaiyvr28HjEGXVMS8pDGbfnrG5WBjBf4hyUDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T10:56:09.155161Z"},"content_sha256":"2cfcada3e80dca6b986427fb4498f6db5c6508c6d45c09f8237705bf8f8154f1","schema_version":"1.0","event_id":"sha256:2cfcada3e80dca6b986427fb4498f6db5c6508c6d45c09f8237705bf8f8154f1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:SOWJ64GEQ7U6Q3JDXW2RN26YJB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Unsupervised Shape Completion via Deep Prior in the Neural Tangent Kernel Perspective","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Hao Pan, Lei Chu, Wenping Wang","submitted_at":"2021-04-19T02:41:15Z","abstract_excerpt":"We present a novel approach for completing and reconstructing 3D shapes from incomplete scanned data by using deep neural networks. Rather than being trained on supervised completion tasks and applied on a testing shape, the network is optimized from scratch on the single testing shape, to fully adapt to the shape and complete the missing data using contextual guidance from the known regions. The ability to complete missing data by an untrained neural network is usually referred to as the deep prior. In this paper, we interpret the deep prior from a neural tangent kernel (NTK) perspective and "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.09023","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/2104.09023/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":"2026-07-05T02:32:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wqjU4F4A4AsfPsT48lz7PWdaOdmNvoDdv5RP3gFzxbKWIDQsKYlfBIMth/p60znjjy1kNGKyvjXIkco0qmD3DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T10:56:09.155675Z"},"content_sha256":"b51d1aeb44f439235784c9baf57a4131b79d5026cf2c85cb131e210dc0a79d00","schema_version":"1.0","event_id":"sha256:b51d1aeb44f439235784c9baf57a4131b79d5026cf2c85cb131e210dc0a79d00"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SOWJ64GEQ7U6Q3JDXW2RN26YJB/bundle.json","state_url":"https://pith.science/pith/SOWJ64GEQ7U6Q3JDXW2RN26YJB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SOWJ64GEQ7U6Q3JDXW2RN26YJB/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":"2026-08-07T10:56:09Z","links":{"resolver":"https://pith.science/pith/SOWJ64GEQ7U6Q3JDXW2RN26YJB","bundle":"https://pith.science/pith/SOWJ64GEQ7U6Q3JDXW2RN26YJB/bundle.json","state":"https://pith.science/pith/SOWJ64GEQ7U6Q3JDXW2RN26YJB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SOWJ64GEQ7U6Q3JDXW2RN26YJB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:SOWJ64GEQ7U6Q3JDXW2RN26YJB","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":"72ae1f2b9344c36138c033162ff3d1f7bd6e53aefda80921b5067f3874628a7b","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-04-19T02:41:15Z","title_canon_sha256":"76be5c05f4679e0827172c0cc52031c8a94bed9a7461e0889d2e8d9c7f6757b0"},"schema_version":"1.0","source":{"id":"2104.09023","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.09023","created_at":"2026-07-05T02:32:58Z"},{"alias_kind":"arxiv_version","alias_value":"2104.09023v1","created_at":"2026-07-05T02:32:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.09023","created_at":"2026-07-05T02:32:58Z"},{"alias_kind":"pith_short_12","alias_value":"SOWJ64GEQ7U6","created_at":"2026-07-05T02:32:58Z"},{"alias_kind":"pith_short_16","alias_value":"SOWJ64GEQ7U6Q3JD","created_at":"2026-07-05T02:32:58Z"},{"alias_kind":"pith_short_8","alias_value":"SOWJ64GE","created_at":"2026-07-05T02:32:58Z"}],"graph_snapshots":[{"event_id":"sha256:b51d1aeb44f439235784c9baf57a4131b79d5026cf2c85cb131e210dc0a79d00","target":"graph","created_at":"2026-07-05T02:32:58Z","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/2104.09023/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present a novel approach for completing and reconstructing 3D shapes from incomplete scanned data by using deep neural networks. Rather than being trained on supervised completion tasks and applied on a testing shape, the network is optimized from scratch on the single testing shape, to fully adapt to the shape and complete the missing data using contextual guidance from the known regions. The ability to complete missing data by an untrained neural network is usually referred to as the deep prior. In this paper, we interpret the deep prior from a neural tangent kernel (NTK) perspective and ","authors_text":"Hao Pan, Lei Chu, Wenping Wang","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-04-19T02:41:15Z","title":"Unsupervised Shape Completion via Deep Prior in the Neural Tangent Kernel Perspective"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.09023","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":"sha256:2cfcada3e80dca6b986427fb4498f6db5c6508c6d45c09f8237705bf8f8154f1","target":"record","created_at":"2026-07-05T02:32:58Z","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":"72ae1f2b9344c36138c033162ff3d1f7bd6e53aefda80921b5067f3874628a7b","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-04-19T02:41:15Z","title_canon_sha256":"76be5c05f4679e0827172c0cc52031c8a94bed9a7461e0889d2e8d9c7f6757b0"},"schema_version":"1.0","source":{"id":"2104.09023","kind":"arxiv","version":1}},"canonical_sha256":"93ac9f70c487e9e86d23bdb516ebd848687027e39ee51ff9ec74c40abda4b04e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"93ac9f70c487e9e86d23bdb516ebd848687027e39ee51ff9ec74c40abda4b04e","first_computed_at":"2026-07-05T02:32:58.060280Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:32:58.060280Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+bYINZ6sUcP2wK1XLnhAGZSEYmq2L9RV9GMYehnztg6SDpR8kbQrDebA1/zYY17/ncb4DTHl5jN8ZyoYFROoAw==","signature_status":"signed_v1","signed_at":"2026-07-05T02:32:58.060697Z","signed_message":"canonical_sha256_bytes"},"source_id":"2104.09023","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2cfcada3e80dca6b986427fb4498f6db5c6508c6d45c09f8237705bf8f8154f1","sha256:b51d1aeb44f439235784c9baf57a4131b79d5026cf2c85cb131e210dc0a79d00"],"state_sha256":"edf770cc0cf8d835bac2dba5441af7e3fcd4704b284d286c38f8cc4ec3141a32"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"p+Wpna5jBG2ZeMBtjJqcNLIJf9e+rRqIZWKbRcKYUJr21GCVnomsQiwkn4+fZLcR8yRxAwr7RlxWVwGF2sHlBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T10:56:09.161428Z","bundle_sha256":"0c3ce4698ff1a6fb84f8967e7b4f9795f6f9c5c64b3ff39d45188141e56fdb45"}}