{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:VXDVIXNCP2TTLRLGRWE7EQRRMK","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":"bf42abe747c7149bb15d75ca76bbb56377964fc593876baed5d799f2acc6b36b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-19T03:06:42Z","title_canon_sha256":"b9c7042dfd72af3b1792611645cf89bbb261a7d6e4e6f093fc0f03c3823a7cbf"},"schema_version":"1.0","source":{"id":"1712.06760","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.06760","created_at":"2026-05-18T00:19:16Z"},{"alias_kind":"arxiv_version","alias_value":"1712.06760v2","created_at":"2026-05-18T00:19:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.06760","created_at":"2026-05-18T00:19:16Z"},{"alias_kind":"pith_short_12","alias_value":"VXDVIXNCP2TT","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_16","alias_value":"VXDVIXNCP2TTLRLG","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_8","alias_value":"VXDVIXNC","created_at":"2026-05-18T12:31:49Z"}],"graph_snapshots":[{"event_id":"sha256:dd332bbbbb93de06b4855a74e0911975073be8cce122ad5ea0e11d3648242b1a","target":"graph","created_at":"2026-05-18T00:19:16Z","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"},"paper":{"abstract_excerpt":"Unlike on images, semantic learning on 3D point clouds using a deep network is challenging due to the naturally unordered data structure. Among existing works, PointNet has achieved promising results by directly learning on point sets. However, it does not take full advantage of a point's local neighborhood that contains fine-grained structural information which turns out to be helpful towards better semantic learning. In this regard, we present two new operations to improve PointNet with a more efficient exploitation of local structures. The first one focuses on local 3D geometric structures.","authors_text":"Chen Feng, Dong Tian, Yaoqing Yang, Yiru Shen","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-19T03:06:42Z","title":"Mining Point Cloud Local Structures by Kernel Correlation and Graph Pooling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.06760","kind":"arxiv","version":2},"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:bc9e4ea21e6b3e7e8695bab3743d017816d18d5b0c249b9de7a6515b4c005d77","target":"record","created_at":"2026-05-18T00:19:16Z","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":"bf42abe747c7149bb15d75ca76bbb56377964fc593876baed5d799f2acc6b36b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-19T03:06:42Z","title_canon_sha256":"b9c7042dfd72af3b1792611645cf89bbb261a7d6e4e6f093fc0f03c3823a7cbf"},"schema_version":"1.0","source":{"id":"1712.06760","kind":"arxiv","version":2}},"canonical_sha256":"adc7545da27ea735c5668d89f242316292a7e21a8ea3ae2cb333f757e70f21ec","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"adc7545da27ea735c5668d89f242316292a7e21a8ea3ae2cb333f757e70f21ec","first_computed_at":"2026-05-18T00:19:16.657331Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:19:16.657331Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Jcwon9fx5foqmxtLbJINntOhvLRwUHZyGpM4Heemj7QAZsOwUSwCY86r8c2do+bz5qd/OUFjwIALHjWqviLjDg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:19:16.658102Z","signed_message":"canonical_sha256_bytes"},"source_id":"1712.06760","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bc9e4ea21e6b3e7e8695bab3743d017816d18d5b0c249b9de7a6515b4c005d77","sha256:dd332bbbbb93de06b4855a74e0911975073be8cce122ad5ea0e11d3648242b1a"],"state_sha256":"f181d0bf2baada4502d9d297cadea7c8c2d5d3f45b92f4f05e00c61339e350f1"}