{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:SNAO4D56K7CYOPQBZPMK5DH45U","short_pith_number":"pith:SNAO4D56","canonical_record":{"source":{"id":"1905.04757","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-05-12T17:58:55Z","cross_cats_sorted":[],"title_canon_sha256":"b350ae982cf8dfe2a91ffe4430640742e730f52e3c70843bbff227c67ca6557e","abstract_canon_sha256":"c12ce40042e94e88c34b6ceb38b49b50bd2a1ee3d1e5fb80a8ff81853dc4da37"},"schema_version":"1.0"},"canonical_sha256":"9340ee0fbe57c5873e01cbd8ae8cfced1f3e0d760f68abe4a83dee3f50d68eca","source":{"kind":"arxiv","id":"1905.04757","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.04757","created_at":"2026-05-17T23:43:49Z"},{"alias_kind":"arxiv_version","alias_value":"1905.04757v2","created_at":"2026-05-17T23:43:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.04757","created_at":"2026-05-17T23:43:49Z"},{"alias_kind":"pith_short_12","alias_value":"SNAO4D56K7CY","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_16","alias_value":"SNAO4D56K7CYOPQB","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_8","alias_value":"SNAO4D56","created_at":"2026-05-18T12:33:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:SNAO4D56K7CYOPQBZPMK5DH45U","target":"record","payload":{"canonical_record":{"source":{"id":"1905.04757","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-05-12T17:58:55Z","cross_cats_sorted":[],"title_canon_sha256":"b350ae982cf8dfe2a91ffe4430640742e730f52e3c70843bbff227c67ca6557e","abstract_canon_sha256":"c12ce40042e94e88c34b6ceb38b49b50bd2a1ee3d1e5fb80a8ff81853dc4da37"},"schema_version":"1.0"},"canonical_sha256":"9340ee0fbe57c5873e01cbd8ae8cfced1f3e0d760f68abe4a83dee3f50d68eca","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:43:49.382811Z","signature_b64":"QEqCA7y2W10d6N54t5mkl/dQHQWZ0C6s4Vb/usywnd5Kg6QFLWFJSNuoVQ4cAmxRCceQqpYGF9JWocfjzohbAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9340ee0fbe57c5873e01cbd8ae8cfced1f3e0d760f68abe4a83dee3f50d68eca","last_reissued_at":"2026-05-17T23:43:49.382285Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:43:49.382285Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1905.04757","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:43:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yT8JnJQG7RZ5f1Gk6KuZq/qDYhbUfJS9HXqavVuH7nmvwNM+oa8tB/lQ0iO7yZGCFgLomIlfZYhOdnrtrHVMDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-29T21:47:39.672871Z"},"content_sha256":"461bd08e2455133266547413d15e604b36086a9b550a9c69895f09b3277d5a54","schema_version":"1.0","event_id":"sha256:461bd08e2455133266547413d15e604b36086a9b550a9c69895f09b3277d5a54"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:SNAO4D56K7CYOPQBZPMK5DH45U","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Alex C. Kot, Amir Shahroudy, Gang Wang, Jun Liu, Ling-Yu Duan, Mauricio Perez","submitted_at":"2019-05-12T17:58:55Z","abstract_excerpt":"Research on depth-based human activity analysis achieved outstanding performance and demonstrated the effectiveness of 3D representation for action recognition. The existing depth-based and RGB+D-based action recognition benchmarks have a number of limitations, including the lack of large-scale training samples, realistic number of distinct class categories, diversity in camera views, varied environmental conditions, and variety of human subjects. In this work, we introduce a large-scale dataset for RGB+D human action recognition, which is collected from 106 distinct subjects and contains more"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.04757","kind":"arxiv","version":2},"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":"2026-05-17T23:43:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HAlz7wWiLEMfe1+iXWxCaLKg5RCHZibeVKHsCzTQHbt1yOG1JYlRJm3o8Osjhq0zW/fEu9LH6jcNKbBkbJ7hBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-29T21:47:39.673559Z"},"content_sha256":"89e77e4a6ad825878e5d52421ef360627e45e1e4f2bac995a46133ec757dfef3","schema_version":"1.0","event_id":"sha256:89e77e4a6ad825878e5d52421ef360627e45e1e4f2bac995a46133ec757dfef3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SNAO4D56K7CYOPQBZPMK5DH45U/bundle.json","state_url":"https://pith.science/pith/SNAO4D56K7CYOPQBZPMK5DH45U/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SNAO4D56K7CYOPQBZPMK5DH45U/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":"2026-05-29T21:47:39Z","links":{"resolver":"https://pith.science/pith/SNAO4D56K7CYOPQBZPMK5DH45U","bundle":"https://pith.science/pith/SNAO4D56K7CYOPQBZPMK5DH45U/bundle.json","state":"https://pith.science/pith/SNAO4D56K7CYOPQBZPMK5DH45U/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SNAO4D56K7CYOPQBZPMK5DH45U/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:SNAO4D56K7CYOPQBZPMK5DH45U","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":"c12ce40042e94e88c34b6ceb38b49b50bd2a1ee3d1e5fb80a8ff81853dc4da37","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-05-12T17:58:55Z","title_canon_sha256":"b350ae982cf8dfe2a91ffe4430640742e730f52e3c70843bbff227c67ca6557e"},"schema_version":"1.0","source":{"id":"1905.04757","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.04757","created_at":"2026-05-17T23:43:49Z"},{"alias_kind":"arxiv_version","alias_value":"1905.04757v2","created_at":"2026-05-17T23:43:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.04757","created_at":"2026-05-17T23:43:49Z"},{"alias_kind":"pith_short_12","alias_value":"SNAO4D56K7CY","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_16","alias_value":"SNAO4D56K7CYOPQB","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_8","alias_value":"SNAO4D56","created_at":"2026-05-18T12:33:27Z"}],"graph_snapshots":[{"event_id":"sha256:89e77e4a6ad825878e5d52421ef360627e45e1e4f2bac995a46133ec757dfef3","target":"graph","created_at":"2026-05-17T23:43:49Z","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":"Research on depth-based human activity analysis achieved outstanding performance and demonstrated the effectiveness of 3D representation for action recognition. The existing depth-based and RGB+D-based action recognition benchmarks have a number of limitations, including the lack of large-scale training samples, realistic number of distinct class categories, diversity in camera views, varied environmental conditions, and variety of human subjects. In this work, we introduce a large-scale dataset for RGB+D human action recognition, which is collected from 106 distinct subjects and contains more","authors_text":"Alex C. Kot, Amir Shahroudy, Gang Wang, Jun Liu, Ling-Yu Duan, Mauricio Perez","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-05-12T17:58:55Z","title":"NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.04757","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":"sha256:461bd08e2455133266547413d15e604b36086a9b550a9c69895f09b3277d5a54","target":"record","created_at":"2026-05-17T23:43:49Z","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":"c12ce40042e94e88c34b6ceb38b49b50bd2a1ee3d1e5fb80a8ff81853dc4da37","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-05-12T17:58:55Z","title_canon_sha256":"b350ae982cf8dfe2a91ffe4430640742e730f52e3c70843bbff227c67ca6557e"},"schema_version":"1.0","source":{"id":"1905.04757","kind":"arxiv","version":2}},"canonical_sha256":"9340ee0fbe57c5873e01cbd8ae8cfced1f3e0d760f68abe4a83dee3f50d68eca","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9340ee0fbe57c5873e01cbd8ae8cfced1f3e0d760f68abe4a83dee3f50d68eca","first_computed_at":"2026-05-17T23:43:49.382285Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:43:49.382285Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QEqCA7y2W10d6N54t5mkl/dQHQWZ0C6s4Vb/usywnd5Kg6QFLWFJSNuoVQ4cAmxRCceQqpYGF9JWocfjzohbAA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:43:49.382811Z","signed_message":"canonical_sha256_bytes"},"source_id":"1905.04757","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:461bd08e2455133266547413d15e604b36086a9b550a9c69895f09b3277d5a54","sha256:89e77e4a6ad825878e5d52421ef360627e45e1e4f2bac995a46133ec757dfef3"],"state_sha256":"0b0c194e1efa12b1fb64576fff60c00854f5589df3111b71bebdb56a9ff05495"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0cGSau5Zo5Pyn/Kr9vtVolws6lIDv7hm/fUjn/jWcChsksEsvzsg0Wdxyz0pz6Ba2w8te1vu54/XISpkJvgDAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-29T21:47:39.677675Z","bundle_sha256":"ead9234c0a7ff2299c3a14d75981ab6f82f4f577c3d231279a9881dd1d2dddc0"}}