{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:A5FVBQZUPYAQAZOI3EUIVCVFI7","short_pith_number":"pith:A5FVBQZU","canonical_record":{"source":{"id":"1904.04231","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-08T17:57:27Z","cross_cats_sorted":[],"title_canon_sha256":"cc1a32bea0debd332ac06d07a90b8f803188d37d04447813fb2c9efd2853a62a","abstract_canon_sha256":"b417560af8485d607585f2eb630faa1abc89c8918f9fed12ec3a08cded71d4de"},"schema_version":"1.0"},"canonical_sha256":"074b50c3347e010065c8d9288a8aa547c1a2215e0ca76f509c460e2480a6ddfb","source":{"kind":"arxiv","id":"1904.04231","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.04231","created_at":"2026-05-17T23:49:06Z"},{"alias_kind":"arxiv_version","alias_value":"1904.04231v1","created_at":"2026-05-17T23:49:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.04231","created_at":"2026-05-17T23:49:06Z"},{"alias_kind":"pith_short_12","alias_value":"A5FVBQZUPYAQ","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"A5FVBQZUPYAQAZOI","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"A5FVBQZU","created_at":"2026-05-18T12:33:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:A5FVBQZUPYAQAZOI3EUIVCVFI7","target":"record","payload":{"canonical_record":{"source":{"id":"1904.04231","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-08T17:57:27Z","cross_cats_sorted":[],"title_canon_sha256":"cc1a32bea0debd332ac06d07a90b8f803188d37d04447813fb2c9efd2853a62a","abstract_canon_sha256":"b417560af8485d607585f2eb630faa1abc89c8918f9fed12ec3a08cded71d4de"},"schema_version":"1.0"},"canonical_sha256":"074b50c3347e010065c8d9288a8aa547c1a2215e0ca76f509c460e2480a6ddfb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:49:06.694909Z","signature_b64":"r5RzoZxBwDEN7pl68twwRMKs6E2hDJ0uuQ8TPkiqhW5tTOVTRayMFUGn2BY6R7vnMn2/5VyaoL1gL4LYcE3fBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"074b50c3347e010065c8d9288a8aa547c1a2215e0ca76f509c460e2480a6ddfb","last_reissued_at":"2026-05-17T23:49:06.694139Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:49:06.694139Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1904.04231","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":"2026-05-17T23:49:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"psIW5J73Oa+1Jt7juKRtUhXOzTcgMv+W7lGj7rxz3t553FYdXen/UKS0WW0EEcGnEdTUPLQvq4tBwNNa3JiPBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-19T22:03:03.601262Z"},"content_sha256":"427dafadfe22b9eaacd647def056abb6cca926092ce9557b3161947f289fccb9","schema_version":"1.0","event_id":"sha256:427dafadfe22b9eaacd647def056abb6cca926092ce9557b3161947f289fccb9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:A5FVBQZUPYAQAZOI3EUIVCVFI7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Relational Action Forecasting","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Abhinav Shrivastava, Carl Vondrick, Chen Sun, Cordelia Schmid, Kevin Murphy, Rahul Sukthankar","submitted_at":"2019-04-08T17:57:27Z","abstract_excerpt":"This paper focuses on multi-person action forecasting in videos. More precisely, given a history of H previous frames, the goal is to detect actors and to predict their future actions for the next T frames. Our approach jointly models temporal and spatial interactions among different actors by constructing a recurrent graph, using actor proposals obtained with Faster R-CNN as nodes. Our method learns to select a subset of discriminative relations without requiring explicit supervision, thus enabling us to tackle challenging visual data. We refer to our model as Discriminative Relational Recurr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.04231","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":""},"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":"2026-05-17T23:49:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5ADkWiAc9qBtYqoHIEs9lOaJ3Z6NxnrNJpD4Yf874tH9QEpkRXU74/xc3ifXhslozQXv063TcqN9X3L/9GA2BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-19T22:03:03.601623Z"},"content_sha256":"367c958b35dd6cc5fad89f9e4b5bb27829dd50f7a8487f16a987e3723bd35a54","schema_version":"1.0","event_id":"sha256:367c958b35dd6cc5fad89f9e4b5bb27829dd50f7a8487f16a987e3723bd35a54"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/A5FVBQZUPYAQAZOI3EUIVCVFI7/bundle.json","state_url":"https://pith.science/pith/A5FVBQZUPYAQAZOI3EUIVCVFI7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/A5FVBQZUPYAQAZOI3EUIVCVFI7/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":"2026-05-19T22:03:03Z","links":{"resolver":"https://pith.science/pith/A5FVBQZUPYAQAZOI3EUIVCVFI7","bundle":"https://pith.science/pith/A5FVBQZUPYAQAZOI3EUIVCVFI7/bundle.json","state":"https://pith.science/pith/A5FVBQZUPYAQAZOI3EUIVCVFI7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/A5FVBQZUPYAQAZOI3EUIVCVFI7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:A5FVBQZUPYAQAZOI3EUIVCVFI7","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":"b417560af8485d607585f2eb630faa1abc89c8918f9fed12ec3a08cded71d4de","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-08T17:57:27Z","title_canon_sha256":"cc1a32bea0debd332ac06d07a90b8f803188d37d04447813fb2c9efd2853a62a"},"schema_version":"1.0","source":{"id":"1904.04231","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.04231","created_at":"2026-05-17T23:49:06Z"},{"alias_kind":"arxiv_version","alias_value":"1904.04231v1","created_at":"2026-05-17T23:49:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.04231","created_at":"2026-05-17T23:49:06Z"},{"alias_kind":"pith_short_12","alias_value":"A5FVBQZUPYAQ","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"A5FVBQZUPYAQAZOI","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"A5FVBQZU","created_at":"2026-05-18T12:33:12Z"}],"graph_snapshots":[{"event_id":"sha256:367c958b35dd6cc5fad89f9e4b5bb27829dd50f7a8487f16a987e3723bd35a54","target":"graph","created_at":"2026-05-17T23:49:06Z","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":"This paper focuses on multi-person action forecasting in videos. More precisely, given a history of H previous frames, the goal is to detect actors and to predict their future actions for the next T frames. Our approach jointly models temporal and spatial interactions among different actors by constructing a recurrent graph, using actor proposals obtained with Faster R-CNN as nodes. Our method learns to select a subset of discriminative relations without requiring explicit supervision, thus enabling us to tackle challenging visual data. We refer to our model as Discriminative Relational Recurr","authors_text":"Abhinav Shrivastava, Carl Vondrick, Chen Sun, Cordelia Schmid, Kevin Murphy, Rahul Sukthankar","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-08T17:57:27Z","title":"Relational Action Forecasting"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.04231","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":"sha256:427dafadfe22b9eaacd647def056abb6cca926092ce9557b3161947f289fccb9","target":"record","created_at":"2026-05-17T23:49:06Z","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":"b417560af8485d607585f2eb630faa1abc89c8918f9fed12ec3a08cded71d4de","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-08T17:57:27Z","title_canon_sha256":"cc1a32bea0debd332ac06d07a90b8f803188d37d04447813fb2c9efd2853a62a"},"schema_version":"1.0","source":{"id":"1904.04231","kind":"arxiv","version":1}},"canonical_sha256":"074b50c3347e010065c8d9288a8aa547c1a2215e0ca76f509c460e2480a6ddfb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"074b50c3347e010065c8d9288a8aa547c1a2215e0ca76f509c460e2480a6ddfb","first_computed_at":"2026-05-17T23:49:06.694139Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:49:06.694139Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"r5RzoZxBwDEN7pl68twwRMKs6E2hDJ0uuQ8TPkiqhW5tTOVTRayMFUGn2BY6R7vnMn2/5VyaoL1gL4LYcE3fBg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:49:06.694909Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.04231","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:427dafadfe22b9eaacd647def056abb6cca926092ce9557b3161947f289fccb9","sha256:367c958b35dd6cc5fad89f9e4b5bb27829dd50f7a8487f16a987e3723bd35a54"],"state_sha256":"34fa05adb40c0b2b26a99afe667f17fbc5d3dde0857a26ee57c8a65c5b100979"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dX/CBJkX7PwwwGY0dYpygOzgCogFNlHRxc8LwdrzIq+1XqBQOQsDhCxIWNq7wY+pulr3BZNwb91zWM6bAoN7DQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-19T22:03:03.603609Z","bundle_sha256":"1f4fc3af2be205cc68a34c3ebb88d601598da7a149447f56d23ff6026b0c5484"}}