{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:ZSEELKNKZBOJTYSJ4KLJUCNN2F","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":"dfbd5c7e540f48af72bec3bdb548d3652cf5491eddcf83178430d383051c7150","cross_cats_sorted":["cs.LG","cs.RO","eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-11-28T22:37:06Z","title_canon_sha256":"8f8f953f5b8cc7e53a6b829c487f49966aaa9c816270ec6173aec02a0b1f59c5"},"schema_version":"1.0","source":{"id":"1911.12885","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1911.12885","created_at":"2026-07-05T02:31:17Z"},{"alias_kind":"arxiv_version","alias_value":"1911.12885v5","created_at":"2026-07-05T02:31:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1911.12885","created_at":"2026-07-05T02:31:17Z"},{"alias_kind":"pith_short_12","alias_value":"ZSEELKNKZBOJ","created_at":"2026-07-05T02:31:17Z"},{"alias_kind":"pith_short_16","alias_value":"ZSEELKNKZBOJTYSJ","created_at":"2026-07-05T02:31:17Z"},{"alias_kind":"pith_short_8","alias_value":"ZSEELKNK","created_at":"2026-07-05T02:31:17Z"}],"graph_snapshots":[{"event_id":"sha256:78871881bb0180f8a07c44bb66eac7e19d4dce0357e9d262cccec4470ff3bd77","target":"graph","created_at":"2026-07-05T02:31:17Z","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/1911.12885/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"As the basic task of point cloud analysis, classification is fundamental but always challenging. To address some unsolved problems of existing methods, we propose a network that captures geometric features of point clouds for better representations. To achieve this, on the one hand, we enrich the geometric information of points in low-level 3D space explicitly. On the other hand, we apply CNN-based structures in high-level feature spaces to learn local geometric context implicitly. Specifically, we leverage an idea of error-correcting feedback structure to capture the local features of point c","authors_text":"Nick Barnes, Saeed Anwar, Shi Qiu","cross_cats":["cs.LG","cs.RO","eess.IV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-11-28T22:37:06Z","title":"Geometric Back-projection Network for Point Cloud Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1911.12885","kind":"arxiv","version":5},"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":"sha256:4da9a5078510dbbd231ec8a633e012225f20502472ae8a33576550b84431b7c3","target":"record","created_at":"2026-07-05T02:31:17Z","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":"dfbd5c7e540f48af72bec3bdb548d3652cf5491eddcf83178430d383051c7150","cross_cats_sorted":["cs.LG","cs.RO","eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-11-28T22:37:06Z","title_canon_sha256":"8f8f953f5b8cc7e53a6b829c487f49966aaa9c816270ec6173aec02a0b1f59c5"},"schema_version":"1.0","source":{"id":"1911.12885","kind":"arxiv","version":5}},"canonical_sha256":"cc8845a9aac85c99e249e2969a09add162123c6f2b999cc10c3ec67b5d4f57c9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cc8845a9aac85c99e249e2969a09add162123c6f2b999cc10c3ec67b5d4f57c9","first_computed_at":"2026-07-05T02:31:17.019784Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:31:17.019784Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6wpwgLQTVqDvu85oFyFRN627KXmMk74fFYQkgOW0IrI+sDquC/2wn86hcw/a1QPTpow+emCnKUWDgt3uK6ptAw==","signature_status":"signed_v1","signed_at":"2026-07-05T02:31:17.020291Z","signed_message":"canonical_sha256_bytes"},"source_id":"1911.12885","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4da9a5078510dbbd231ec8a633e012225f20502472ae8a33576550b84431b7c3","sha256:78871881bb0180f8a07c44bb66eac7e19d4dce0357e9d262cccec4470ff3bd77"],"state_sha256":"6a82328eb96c249173796708215272b177b92e0ab38dc58280ca230032dffc2f"}