{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:47LI6RMHLMD56DKBQK5ECICHEQ","short_pith_number":"pith:47LI6RMH","canonical_record":{"source":{"id":"2012.06399","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-12-11T14:58:21Z","cross_cats_sorted":[],"title_canon_sha256":"9e7957df48eb697abaaeacb70c22d10f2c21b392987a3e7f591317a4952b572f","abstract_canon_sha256":"5a6c7f4c7ec7da8bac1a9b3c72aef0619fc77cc55cc25003f66d7f53e22c7fa9"},"schema_version":"1.0"},"canonical_sha256":"e7d68f45875b07df0d4182ba412047240e8e376bb4eecbb93c1a9bc9b171488c","source":{"kind":"arxiv","id":"2012.06399","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2012.06399","created_at":"2026-07-05T02:51:37Z"},{"alias_kind":"arxiv_version","alias_value":"2012.06399v1","created_at":"2026-07-05T02:51:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2012.06399","created_at":"2026-07-05T02:51:37Z"},{"alias_kind":"pith_short_12","alias_value":"47LI6RMHLMD5","created_at":"2026-07-05T02:51:37Z"},{"alias_kind":"pith_short_16","alias_value":"47LI6RMHLMD56DKB","created_at":"2026-07-05T02:51:37Z"},{"alias_kind":"pith_short_8","alias_value":"47LI6RMH","created_at":"2026-07-05T02:51:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:47LI6RMHLMD56DKBQK5ECICHEQ","target":"record","payload":{"canonical_record":{"source":{"id":"2012.06399","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-12-11T14:58:21Z","cross_cats_sorted":[],"title_canon_sha256":"9e7957df48eb697abaaeacb70c22d10f2c21b392987a3e7f591317a4952b572f","abstract_canon_sha256":"5a6c7f4c7ec7da8bac1a9b3c72aef0619fc77cc55cc25003f66d7f53e22c7fa9"},"schema_version":"1.0"},"canonical_sha256":"e7d68f45875b07df0d4182ba412047240e8e376bb4eecbb93c1a9bc9b171488c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:51:37.863607Z","signature_b64":"gxdI30O1FaRehlKFei8oqH6CCbTRATOF/2CA5EShzBt4I0bYUMMhcTOI9eRT/AZ3BAI6meGxmWWWBGpT2PuuCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e7d68f45875b07df0d4182ba412047240e8e376bb4eecbb93c1a9bc9b171488c","last_reissued_at":"2026-07-05T02:51:37.863208Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:51:37.863208Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2012.06399","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":"2026-07-05T02:51:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UXbkqhfOXwlY0JUjg+/5JrNBgp/8Flf2OIGWYfDb42ArMJXSzirlSsHnvmCfaX+iVBDTGnVVOauCK10ZS261Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T02:59:17.126939Z"},"content_sha256":"13a0e970a19b9c34c2c807103f06a96ae3fe29501f6451574ad87e081926e720","schema_version":"1.0","event_id":"sha256:13a0e970a19b9c34c2c807103f06a96ae3fe29501f6451574ad87e081926e720"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:47LI6RMHLMD56DKBQK5ECICHEQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Spatial Temporal Transformer Network for Skeleton-based Action Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chiara Plizzari, Marco Cannici, Matteo Matteucci","submitted_at":"2020-12-11T14:58:21Z","abstract_excerpt":"Skeleton-based human action recognition has achieved a great interest in recent years, as skeleton data has been demonstrated to be robust to illumination changes, body scales, dynamic camera views, and complex background. Nevertheless, an effective encoding of the latent information underlying the 3D skeleton is still an open problem. In this work, we propose a novel Spatial-Temporal Transformer network (ST-TR) which models dependencies between joints using the Transformer self-attention operator. In our ST-TR model, a Spatial Self-Attention module (SSA) is used to understand intra-frame inte"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2012.06399","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/2012.06399/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":"2026-07-05T02:51:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GE9LIpn+L2Gjy+ctPd99Ct/dWUKiFNhz1vJatoAYUUEykiJPYKE9dsEiGd9vaEineejcwz5n1IYK9yKWvmIhDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T02:59:17.127430Z"},"content_sha256":"4e7853f7c3649395b95fbc51adb6673f5c81a76beabb65240d73b102f0bd15dd","schema_version":"1.0","event_id":"sha256:4e7853f7c3649395b95fbc51adb6673f5c81a76beabb65240d73b102f0bd15dd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/47LI6RMHLMD56DKBQK5ECICHEQ/bundle.json","state_url":"https://pith.science/pith/47LI6RMHLMD56DKBQK5ECICHEQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/47LI6RMHLMD56DKBQK5ECICHEQ/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":"2026-08-22T02:59:17Z","links":{"resolver":"https://pith.science/pith/47LI6RMHLMD56DKBQK5ECICHEQ","bundle":"https://pith.science/pith/47LI6RMHLMD56DKBQK5ECICHEQ/bundle.json","state":"https://pith.science/pith/47LI6RMHLMD56DKBQK5ECICHEQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/47LI6RMHLMD56DKBQK5ECICHEQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:47LI6RMHLMD56DKBQK5ECICHEQ","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":"5a6c7f4c7ec7da8bac1a9b3c72aef0619fc77cc55cc25003f66d7f53e22c7fa9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-12-11T14:58:21Z","title_canon_sha256":"9e7957df48eb697abaaeacb70c22d10f2c21b392987a3e7f591317a4952b572f"},"schema_version":"1.0","source":{"id":"2012.06399","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2012.06399","created_at":"2026-07-05T02:51:37Z"},{"alias_kind":"arxiv_version","alias_value":"2012.06399v1","created_at":"2026-07-05T02:51:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2012.06399","created_at":"2026-07-05T02:51:37Z"},{"alias_kind":"pith_short_12","alias_value":"47LI6RMHLMD5","created_at":"2026-07-05T02:51:37Z"},{"alias_kind":"pith_short_16","alias_value":"47LI6RMHLMD56DKB","created_at":"2026-07-05T02:51:37Z"},{"alias_kind":"pith_short_8","alias_value":"47LI6RMH","created_at":"2026-07-05T02:51:37Z"}],"graph_snapshots":[{"event_id":"sha256:4e7853f7c3649395b95fbc51adb6673f5c81a76beabb65240d73b102f0bd15dd","target":"graph","created_at":"2026-07-05T02:51:37Z","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/2012.06399/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Skeleton-based human action recognition has achieved a great interest in recent years, as skeleton data has been demonstrated to be robust to illumination changes, body scales, dynamic camera views, and complex background. Nevertheless, an effective encoding of the latent information underlying the 3D skeleton is still an open problem. In this work, we propose a novel Spatial-Temporal Transformer network (ST-TR) which models dependencies between joints using the Transformer self-attention operator. In our ST-TR model, a Spatial Self-Attention module (SSA) is used to understand intra-frame inte","authors_text":"Chiara Plizzari, Marco Cannici, Matteo Matteucci","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-12-11T14:58:21Z","title":"Spatial Temporal Transformer Network for Skeleton-based Action Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2012.06399","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":"sha256:13a0e970a19b9c34c2c807103f06a96ae3fe29501f6451574ad87e081926e720","target":"record","created_at":"2026-07-05T02:51:37Z","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":"5a6c7f4c7ec7da8bac1a9b3c72aef0619fc77cc55cc25003f66d7f53e22c7fa9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-12-11T14:58:21Z","title_canon_sha256":"9e7957df48eb697abaaeacb70c22d10f2c21b392987a3e7f591317a4952b572f"},"schema_version":"1.0","source":{"id":"2012.06399","kind":"arxiv","version":1}},"canonical_sha256":"e7d68f45875b07df0d4182ba412047240e8e376bb4eecbb93c1a9bc9b171488c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e7d68f45875b07df0d4182ba412047240e8e376bb4eecbb93c1a9bc9b171488c","first_computed_at":"2026-07-05T02:51:37.863208Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:51:37.863208Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"gxdI30O1FaRehlKFei8oqH6CCbTRATOF/2CA5EShzBt4I0bYUMMhcTOI9eRT/AZ3BAI6meGxmWWWBGpT2PuuCA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:51:37.863607Z","signed_message":"canonical_sha256_bytes"},"source_id":"2012.06399","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:13a0e970a19b9c34c2c807103f06a96ae3fe29501f6451574ad87e081926e720","sha256:4e7853f7c3649395b95fbc51adb6673f5c81a76beabb65240d73b102f0bd15dd"],"state_sha256":"78f278c37f344967a20e5035355235e3f2173bf570320b994a1d93fc77429af3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"p6CeYVV7hlYz/HVNC6PZ9+9HhvqjtYFYhCChXweTgVSlhseziLGFJKzB6YzWvuoqZ4E68IlI9IV3IVAQeDa/AQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T02:59:17.132133Z","bundle_sha256":"5183d338a9a3439f65fec1ba6f96f5ac2444f118e67ea56a13664e406fab01e0"}}