{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:RDGT3P2WE5CDRZDWUOFRLLS3KJ","short_pith_number":"pith:RDGT3P2W","canonical_record":{"source":{"id":"1604.00427","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-04-01T22:37:28Z","cross_cats_sorted":[],"title_canon_sha256":"b07686bb1bb90a424bc478e5023dcb5ab8cb0e56d5d5acb4ebac4fc97e22ffd9","abstract_canon_sha256":"5e5e931eee94840515f1c6a4dd9dbd653e72ffbea273e8c2ca7eba9c4110b757"},"schema_version":"1.0"},"canonical_sha256":"88cd3dbf56274438e476a38b15ae5b52518d1c6106b4a1e511aed985991c1eb0","source":{"kind":"arxiv","id":"1604.00427","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1604.00427","created_at":"2026-05-18T01:17:49Z"},{"alias_kind":"arxiv_version","alias_value":"1604.00427v1","created_at":"2026-05-18T01:17:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1604.00427","created_at":"2026-05-18T01:17:49Z"},{"alias_kind":"pith_short_12","alias_value":"RDGT3P2WE5CD","created_at":"2026-05-18T12:30:41Z"},{"alias_kind":"pith_short_16","alias_value":"RDGT3P2WE5CDRZDW","created_at":"2026-05-18T12:30:41Z"},{"alias_kind":"pith_short_8","alias_value":"RDGT3P2W","created_at":"2026-05-18T12:30:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:RDGT3P2WE5CDRZDWUOFRLLS3KJ","target":"record","payload":{"canonical_record":{"source":{"id":"1604.00427","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-04-01T22:37:28Z","cross_cats_sorted":[],"title_canon_sha256":"b07686bb1bb90a424bc478e5023dcb5ab8cb0e56d5d5acb4ebac4fc97e22ffd9","abstract_canon_sha256":"5e5e931eee94840515f1c6a4dd9dbd653e72ffbea273e8c2ca7eba9c4110b757"},"schema_version":"1.0"},"canonical_sha256":"88cd3dbf56274438e476a38b15ae5b52518d1c6106b4a1e511aed985991c1eb0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:17:49.651951Z","signature_b64":"51mv+frRK23sNUG7YGX5mzwaIjzI0CapgMLK2NFoLxKxkWzUoA6/9aJ6RtXdVyLhqsKg09jke3A4DBKKrpeLAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"88cd3dbf56274438e476a38b15ae5b52518d1c6106b4a1e511aed985991c1eb0","last_reissued_at":"2026-05-18T01:17:49.651283Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:17:49.651283Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1604.00427","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":"2026-05-18T01:17:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IFGLmYVerv9Knsm147qXRzA0gls2RiQ1DxcsPqPyPq8ZIr+uetgwsQGgfEEJrLDZX2vnpd7g+rh2eCeQpB7bAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T10:34:38.277336Z"},"content_sha256":"5df446c07c5b7e851035ca012affe3b83b9368774e1c00209253f9e7183f22b2","schema_version":"1.0","event_id":"sha256:5df446c07c5b7e851035ca012affe3b83b9368774e1c00209253f9e7183f22b2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:RDGT3P2WE5CDRZDWUOFRLLS3KJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Leaving Some Stones Unturned: Dynamic Feature Prioritization for Activity Detection in Streaming Video","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Kristen Grauman, Yu-Chuan Su","submitted_at":"2016-04-01T22:37:28Z","abstract_excerpt":"Current approaches for activity recognition often ignore constraints on computational resources: 1) they rely on extensive feature computation to obtain rich descriptors on all frames, and 2) they assume batch-mode access to the entire test video at once. We propose a new active approach to activity recognition that prioritizes \"what to compute when\" in order to make timely predictions. The main idea is to learn a policy that dynamically schedules the sequence of features to compute on selected frames of a given test video. In contrast to traditional static feature selection, our approach cont"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1604.00427","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":"2026-05-18T01:17:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"urD+18bR/wMvRgMoH4BUzWZpAUSCxiPMJgVpEnCzQANAVQ9U4xcr5i5s5/3ARgDoRsXhvcOikBSGbBCRERJFAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T10:34:38.277696Z"},"content_sha256":"403e4b6874d47e8a09e862bdaac23f6e22075721b68e21a653a5110fb3c85149","schema_version":"1.0","event_id":"sha256:403e4b6874d47e8a09e862bdaac23f6e22075721b68e21a653a5110fb3c85149"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RDGT3P2WE5CDRZDWUOFRLLS3KJ/bundle.json","state_url":"https://pith.science/pith/RDGT3P2WE5CDRZDWUOFRLLS3KJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RDGT3P2WE5CDRZDWUOFRLLS3KJ/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":"2026-05-27T10:34:38Z","links":{"resolver":"https://pith.science/pith/RDGT3P2WE5CDRZDWUOFRLLS3KJ","bundle":"https://pith.science/pith/RDGT3P2WE5CDRZDWUOFRLLS3KJ/bundle.json","state":"https://pith.science/pith/RDGT3P2WE5CDRZDWUOFRLLS3KJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RDGT3P2WE5CDRZDWUOFRLLS3KJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:RDGT3P2WE5CDRZDWUOFRLLS3KJ","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":"5e5e931eee94840515f1c6a4dd9dbd653e72ffbea273e8c2ca7eba9c4110b757","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-04-01T22:37:28Z","title_canon_sha256":"b07686bb1bb90a424bc478e5023dcb5ab8cb0e56d5d5acb4ebac4fc97e22ffd9"},"schema_version":"1.0","source":{"id":"1604.00427","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1604.00427","created_at":"2026-05-18T01:17:49Z"},{"alias_kind":"arxiv_version","alias_value":"1604.00427v1","created_at":"2026-05-18T01:17:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1604.00427","created_at":"2026-05-18T01:17:49Z"},{"alias_kind":"pith_short_12","alias_value":"RDGT3P2WE5CD","created_at":"2026-05-18T12:30:41Z"},{"alias_kind":"pith_short_16","alias_value":"RDGT3P2WE5CDRZDW","created_at":"2026-05-18T12:30:41Z"},{"alias_kind":"pith_short_8","alias_value":"RDGT3P2W","created_at":"2026-05-18T12:30:41Z"}],"graph_snapshots":[{"event_id":"sha256:403e4b6874d47e8a09e862bdaac23f6e22075721b68e21a653a5110fb3c85149","target":"graph","created_at":"2026-05-18T01:17:49Z","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":"Current approaches for activity recognition often ignore constraints on computational resources: 1) they rely on extensive feature computation to obtain rich descriptors on all frames, and 2) they assume batch-mode access to the entire test video at once. We propose a new active approach to activity recognition that prioritizes \"what to compute when\" in order to make timely predictions. The main idea is to learn a policy that dynamically schedules the sequence of features to compute on selected frames of a given test video. In contrast to traditional static feature selection, our approach cont","authors_text":"Kristen Grauman, Yu-Chuan Su","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-04-01T22:37:28Z","title":"Leaving Some Stones Unturned: Dynamic Feature Prioritization for Activity Detection in Streaming Video"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1604.00427","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":"sha256:5df446c07c5b7e851035ca012affe3b83b9368774e1c00209253f9e7183f22b2","target":"record","created_at":"2026-05-18T01:17:49Z","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":"5e5e931eee94840515f1c6a4dd9dbd653e72ffbea273e8c2ca7eba9c4110b757","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-04-01T22:37:28Z","title_canon_sha256":"b07686bb1bb90a424bc478e5023dcb5ab8cb0e56d5d5acb4ebac4fc97e22ffd9"},"schema_version":"1.0","source":{"id":"1604.00427","kind":"arxiv","version":1}},"canonical_sha256":"88cd3dbf56274438e476a38b15ae5b52518d1c6106b4a1e511aed985991c1eb0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"88cd3dbf56274438e476a38b15ae5b52518d1c6106b4a1e511aed985991c1eb0","first_computed_at":"2026-05-18T01:17:49.651283Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:17:49.651283Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"51mv+frRK23sNUG7YGX5mzwaIjzI0CapgMLK2NFoLxKxkWzUoA6/9aJ6RtXdVyLhqsKg09jke3A4DBKKrpeLAg==","signature_status":"signed_v1","signed_at":"2026-05-18T01:17:49.651951Z","signed_message":"canonical_sha256_bytes"},"source_id":"1604.00427","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5df446c07c5b7e851035ca012affe3b83b9368774e1c00209253f9e7183f22b2","sha256:403e4b6874d47e8a09e862bdaac23f6e22075721b68e21a653a5110fb3c85149"],"state_sha256":"b79d0fb100d91a16540c843f14caae7dbd893841be05973f6042364d5e28d4e8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yWZZnOO4ukuuJ7WgzXs5uAH9SOpub4a3W2j4zy8/W6/vQYm2D2prNVEKY2rL3H8zIEz1XNH/4emB7/iB/imvDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T10:34:38.280136Z","bundle_sha256":"f4e03b22e3af70b845c648b1b4b86a010c9a2363de4d4ac1a501762014af883c"}}