{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:QFAISNK2VNA4TES26OIVJHT2RP","short_pith_number":"pith:QFAISNK2","canonical_record":{"source":{"id":"1805.02556","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-07T14:59:54Z","cross_cats_sorted":[],"title_canon_sha256":"2b5f45cd7b70ecb2591935d32ff0b786a2f95cd804938dea7381f569b7a98bcb","abstract_canon_sha256":"9c1521225db61985be424bd470991db4e5a376f83833e0d659d8c5c2f525e5f5"},"schema_version":"1.0"},"canonical_sha256":"814089355aab41c9925af391549e7a8bfd3d1a6a1501facbf4843c551cb3e50d","source":{"kind":"arxiv","id":"1805.02556","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.02556","created_at":"2026-05-17T23:48:52Z"},{"alias_kind":"arxiv_version","alias_value":"1805.02556v4","created_at":"2026-05-17T23:48:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.02556","created_at":"2026-05-17T23:48:52Z"},{"alias_kind":"pith_short_12","alias_value":"QFAISNK2VNA4","created_at":"2026-05-18T12:32:46Z"},{"alias_kind":"pith_short_16","alias_value":"QFAISNK2VNA4TES2","created_at":"2026-05-18T12:32:46Z"},{"alias_kind":"pith_short_8","alias_value":"QFAISNK2","created_at":"2026-05-18T12:32:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:QFAISNK2VNA4TES26OIVJHT2RP","target":"record","payload":{"canonical_record":{"source":{"id":"1805.02556","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-07T14:59:54Z","cross_cats_sorted":[],"title_canon_sha256":"2b5f45cd7b70ecb2591935d32ff0b786a2f95cd804938dea7381f569b7a98bcb","abstract_canon_sha256":"9c1521225db61985be424bd470991db4e5a376f83833e0d659d8c5c2f525e5f5"},"schema_version":"1.0"},"canonical_sha256":"814089355aab41c9925af391549e7a8bfd3d1a6a1501facbf4843c551cb3e50d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:48:52.873480Z","signature_b64":"0do0Dm6npZ/XEGfgrYxR9FenrZliRInXzT++c0qaQ7S+w6eRmNXuW+t4IbpgJYIuGNyUqcyV83jovv71q4rLDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"814089355aab41c9925af391549e7a8bfd3d1a6a1501facbf4843c551cb3e50d","last_reissued_at":"2026-05-17T23:48:52.872956Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:48:52.872956Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1805.02556","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:48:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zCvYrNL5LQu0bYWhjQpi2Aq6PC15JZ3dvysz4W0BGEp7r7j3i4IIbVICA97Xxssvo60CaWdHXxsbFSsmgdP/Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T17:08:51.654646Z"},"content_sha256":"b12ef5b4acb91e95304a3eaf88dae18475ae45439b1c06d0f77641b131792da5","schema_version":"1.0","event_id":"sha256:b12ef5b4acb91e95304a3eaf88dae18475ae45439b1c06d0f77641b131792da5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:QFAISNK2VNA4TES26OIVJHT2RP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Relational Network for Skeleton-Based Action Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Liang Wang, Lin Li, Wu Zheng, Yan Huang, Zhaoxiang Zhang","submitted_at":"2018-05-07T14:59:54Z","abstract_excerpt":"With the fast development of effective and low-cost human skeleton capture systems, skeleton-based action recognition has attracted much attention recently. Most existing methods use Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) to extract spatio-temporal information embedded in the skeleton sequences for action recognition. However, these approaches are limited in the ability of relational modeling in a single skeleton, due to the loss of important structural information when converting the raw skeleton data to adapt to the input format of CNN or RNN. In this paper, we"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.02556","kind":"arxiv","version":4},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"2026-05-17T23:48:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iNyjKHfuZiLhaG91Z+Jt31lGDsZ/KCk8sTzRZxz4x7KULuW/4CFSrXNd3XmOTA6vktsGjgb4K/aFjs1yzUJDDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T17:08:51.655303Z"},"content_sha256":"1bcbdb90c8ae751c74df96ca605899f253da48adef7bad2e94c7cded2715197a","schema_version":"1.0","event_id":"sha256:1bcbdb90c8ae751c74df96ca605899f253da48adef7bad2e94c7cded2715197a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QFAISNK2VNA4TES26OIVJHT2RP/bundle.json","state_url":"https://pith.science/pith/QFAISNK2VNA4TES26OIVJHT2RP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QFAISNK2VNA4TES26OIVJHT2RP/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":"2026-06-09T17:08:51Z","links":{"resolver":"https://pith.science/pith/QFAISNK2VNA4TES26OIVJHT2RP","bundle":"https://pith.science/pith/QFAISNK2VNA4TES26OIVJHT2RP/bundle.json","state":"https://pith.science/pith/QFAISNK2VNA4TES26OIVJHT2RP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QFAISNK2VNA4TES26OIVJHT2RP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:QFAISNK2VNA4TES26OIVJHT2RP","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":"9c1521225db61985be424bd470991db4e5a376f83833e0d659d8c5c2f525e5f5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-07T14:59:54Z","title_canon_sha256":"2b5f45cd7b70ecb2591935d32ff0b786a2f95cd804938dea7381f569b7a98bcb"},"schema_version":"1.0","source":{"id":"1805.02556","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.02556","created_at":"2026-05-17T23:48:52Z"},{"alias_kind":"arxiv_version","alias_value":"1805.02556v4","created_at":"2026-05-17T23:48:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.02556","created_at":"2026-05-17T23:48:52Z"},{"alias_kind":"pith_short_12","alias_value":"QFAISNK2VNA4","created_at":"2026-05-18T12:32:46Z"},{"alias_kind":"pith_short_16","alias_value":"QFAISNK2VNA4TES2","created_at":"2026-05-18T12:32:46Z"},{"alias_kind":"pith_short_8","alias_value":"QFAISNK2","created_at":"2026-05-18T12:32:46Z"}],"graph_snapshots":[{"event_id":"sha256:1bcbdb90c8ae751c74df96ca605899f253da48adef7bad2e94c7cded2715197a","target":"graph","created_at":"2026-05-17T23:48:52Z","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":"With the fast development of effective and low-cost human skeleton capture systems, skeleton-based action recognition has attracted much attention recently. Most existing methods use Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) to extract spatio-temporal information embedded in the skeleton sequences for action recognition. However, these approaches are limited in the ability of relational modeling in a single skeleton, due to the loss of important structural information when converting the raw skeleton data to adapt to the input format of CNN or RNN. In this paper, we","authors_text":"Liang Wang, Lin Li, Wu Zheng, Yan Huang, Zhaoxiang Zhang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-07T14:59:54Z","title":"Relational Network for Skeleton-Based Action Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.02556","kind":"arxiv","version":4},"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:b12ef5b4acb91e95304a3eaf88dae18475ae45439b1c06d0f77641b131792da5","target":"record","created_at":"2026-05-17T23:48:52Z","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":"9c1521225db61985be424bd470991db4e5a376f83833e0d659d8c5c2f525e5f5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-07T14:59:54Z","title_canon_sha256":"2b5f45cd7b70ecb2591935d32ff0b786a2f95cd804938dea7381f569b7a98bcb"},"schema_version":"1.0","source":{"id":"1805.02556","kind":"arxiv","version":4}},"canonical_sha256":"814089355aab41c9925af391549e7a8bfd3d1a6a1501facbf4843c551cb3e50d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"814089355aab41c9925af391549e7a8bfd3d1a6a1501facbf4843c551cb3e50d","first_computed_at":"2026-05-17T23:48:52.872956Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:48:52.872956Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0do0Dm6npZ/XEGfgrYxR9FenrZliRInXzT++c0qaQ7S+w6eRmNXuW+t4IbpgJYIuGNyUqcyV83jovv71q4rLDA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:48:52.873480Z","signed_message":"canonical_sha256_bytes"},"source_id":"1805.02556","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b12ef5b4acb91e95304a3eaf88dae18475ae45439b1c06d0f77641b131792da5","sha256:1bcbdb90c8ae751c74df96ca605899f253da48adef7bad2e94c7cded2715197a"],"state_sha256":"1ba5e3d194aa3452a83d5d35eb2173958ebbac19ad73eacb0bcc092b5fb91cee"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"e8/aAojdLjkaMfNEG/Vgtal7B+yfKw4cVA+IaniqzkxaZprlbpOuQCofZ3m2fmOQuX4IQqCLIg1eoypufK+wCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-09T17:08:51.658791Z","bundle_sha256":"debc72427b16a96b00cf36c8ed0b6105f20329cab11de0790efff55f84e2a9b7"}}