{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:FFENKRX6QRRQKJODCNYYIYXHU4","short_pith_number":"pith:FFENKRX6","canonical_record":{"source":{"id":"1612.03052","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-12-09T15:20:23Z","cross_cats_sorted":[],"title_canon_sha256":"fe76398a10ff9ac7a6582d49aad727adc6791ddf8fbe33c71e6ebb016ecb460a","abstract_canon_sha256":"0d58061d4b6c54e3143337530c5d763d7eb0a224e3c98160d996474fbb26b100"},"schema_version":"1.0"},"canonical_sha256":"2948d546fe84630525c313718462e7a70fd0579270cf2f54baaeddfaecb3f945","source":{"kind":"arxiv","id":"1612.03052","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1612.03052","created_at":"2026-05-18T00:23:09Z"},{"alias_kind":"arxiv_version","alias_value":"1612.03052v3","created_at":"2026-05-18T00:23:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1612.03052","created_at":"2026-05-18T00:23:09Z"},{"alias_kind":"pith_short_12","alias_value":"FFENKRX6QRRQ","created_at":"2026-05-18T12:30:15Z"},{"alias_kind":"pith_short_16","alias_value":"FFENKRX6QRRQKJOD","created_at":"2026-05-18T12:30:15Z"},{"alias_kind":"pith_short_8","alias_value":"FFENKRX6","created_at":"2026-05-18T12:30:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:FFENKRX6QRRQKJODCNYYIYXHU4","target":"record","payload":{"canonical_record":{"source":{"id":"1612.03052","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-12-09T15:20:23Z","cross_cats_sorted":[],"title_canon_sha256":"fe76398a10ff9ac7a6582d49aad727adc6791ddf8fbe33c71e6ebb016ecb460a","abstract_canon_sha256":"0d58061d4b6c54e3143337530c5d763d7eb0a224e3c98160d996474fbb26b100"},"schema_version":"1.0"},"canonical_sha256":"2948d546fe84630525c313718462e7a70fd0579270cf2f54baaeddfaecb3f945","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:23:09.242211Z","signature_b64":"VzolUm9YYbmShlB0mdwdcBIz9Yo4rPO1tNhDiH87olp79dTfq7EC7VbO9F9EciCpOnT0RZAfUXwwPE2Rby3RAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2948d546fe84630525c313718462e7a70fd0579270cf2f54baaeddfaecb3f945","last_reissued_at":"2026-05-18T00:23:09.241605Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:23:09.241605Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1612.03052","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:23:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GJa8CXv9LYFnaqLKXvoB8VS00QyDCzYimamEUbBy0ynHmzESj7//HjNbnUk+NWVydKcASTpTQqHSiuCK7Pt8DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T14:11:23.378591Z"},"content_sha256":"38ae358e5fe85a8fc61d3f9093752355b3e66491a8c46a4716e16cb44a500b39","schema_version":"1.0","event_id":"sha256:38ae358e5fe85a8fc61d3f9093752355b3e66491a8c46a4716e16cb44a500b39"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:FFENKRX6QRRQKJODCNYYIYXHU4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ActionFlowNet: Learning Motion Representation for Action Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jan Neumann, Joe Yue-Hei Ng, Jonghyun Choi, Larry S. Davis","submitted_at":"2016-12-09T15:20:23Z","abstract_excerpt":"Even with the recent advances in convolutional neural networks (CNN) in various visual recognition tasks, the state-of-the-art action recognition system still relies on hand crafted motion feature such as optical flow to achieve the best performance. We propose a multitask learning model ActionFlowNet to train a single stream network directly from raw pixels to jointly estimate optical flow while recognizing actions with convolutional neural networks, capturing both appearance and motion in a single model. We additionally provide insights to how the quality of the learned optical flow affects "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1612.03052","kind":"arxiv","version":3},"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":"2026-05-18T00:23:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oikgqzoa0qRVLlLpTh2Aq/8vzQuShin09nEAzpfjl22qMVANbaT6nEzi9f1l2VBGVoDftJHHQH4a4DA0MlR0Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T14:11:23.378947Z"},"content_sha256":"d45c96f9ddef98e14c375cd39d9bbdf452dd36518e69b2b7eed2b0314081ee9e","schema_version":"1.0","event_id":"sha256:d45c96f9ddef98e14c375cd39d9bbdf452dd36518e69b2b7eed2b0314081ee9e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FFENKRX6QRRQKJODCNYYIYXHU4/bundle.json","state_url":"https://pith.science/pith/FFENKRX6QRRQKJODCNYYIYXHU4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FFENKRX6QRRQKJODCNYYIYXHU4/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":"2026-06-30T14:11:23Z","links":{"resolver":"https://pith.science/pith/FFENKRX6QRRQKJODCNYYIYXHU4","bundle":"https://pith.science/pith/FFENKRX6QRRQKJODCNYYIYXHU4/bundle.json","state":"https://pith.science/pith/FFENKRX6QRRQKJODCNYYIYXHU4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FFENKRX6QRRQKJODCNYYIYXHU4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:FFENKRX6QRRQKJODCNYYIYXHU4","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":"0d58061d4b6c54e3143337530c5d763d7eb0a224e3c98160d996474fbb26b100","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-12-09T15:20:23Z","title_canon_sha256":"fe76398a10ff9ac7a6582d49aad727adc6791ddf8fbe33c71e6ebb016ecb460a"},"schema_version":"1.0","source":{"id":"1612.03052","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1612.03052","created_at":"2026-05-18T00:23:09Z"},{"alias_kind":"arxiv_version","alias_value":"1612.03052v3","created_at":"2026-05-18T00:23:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1612.03052","created_at":"2026-05-18T00:23:09Z"},{"alias_kind":"pith_short_12","alias_value":"FFENKRX6QRRQ","created_at":"2026-05-18T12:30:15Z"},{"alias_kind":"pith_short_16","alias_value":"FFENKRX6QRRQKJOD","created_at":"2026-05-18T12:30:15Z"},{"alias_kind":"pith_short_8","alias_value":"FFENKRX6","created_at":"2026-05-18T12:30:15Z"}],"graph_snapshots":[{"event_id":"sha256:d45c96f9ddef98e14c375cd39d9bbdf452dd36518e69b2b7eed2b0314081ee9e","target":"graph","created_at":"2026-05-18T00:23:09Z","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":"Even with the recent advances in convolutional neural networks (CNN) in various visual recognition tasks, the state-of-the-art action recognition system still relies on hand crafted motion feature such as optical flow to achieve the best performance. We propose a multitask learning model ActionFlowNet to train a single stream network directly from raw pixels to jointly estimate optical flow while recognizing actions with convolutional neural networks, capturing both appearance and motion in a single model. We additionally provide insights to how the quality of the learned optical flow affects ","authors_text":"Jan Neumann, Joe Yue-Hei Ng, Jonghyun Choi, Larry S. Davis","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-12-09T15:20:23Z","title":"ActionFlowNet: Learning Motion Representation for Action Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1612.03052","kind":"arxiv","version":3},"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":"sha256:38ae358e5fe85a8fc61d3f9093752355b3e66491a8c46a4716e16cb44a500b39","target":"record","created_at":"2026-05-18T00:23:09Z","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":"0d58061d4b6c54e3143337530c5d763d7eb0a224e3c98160d996474fbb26b100","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-12-09T15:20:23Z","title_canon_sha256":"fe76398a10ff9ac7a6582d49aad727adc6791ddf8fbe33c71e6ebb016ecb460a"},"schema_version":"1.0","source":{"id":"1612.03052","kind":"arxiv","version":3}},"canonical_sha256":"2948d546fe84630525c313718462e7a70fd0579270cf2f54baaeddfaecb3f945","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2948d546fe84630525c313718462e7a70fd0579270cf2f54baaeddfaecb3f945","first_computed_at":"2026-05-18T00:23:09.241605Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:23:09.241605Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VzolUm9YYbmShlB0mdwdcBIz9Yo4rPO1tNhDiH87olp79dTfq7EC7VbO9F9EciCpOnT0RZAfUXwwPE2Rby3RAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:23:09.242211Z","signed_message":"canonical_sha256_bytes"},"source_id":"1612.03052","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:38ae358e5fe85a8fc61d3f9093752355b3e66491a8c46a4716e16cb44a500b39","sha256:d45c96f9ddef98e14c375cd39d9bbdf452dd36518e69b2b7eed2b0314081ee9e"],"state_sha256":"2570688badea16595ba0614381e02384c8b260f9b5b5c40602c934fb928183b6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"L9j2rt7f3h/wJ9H8wxWHq3L/u9nmwDXe3dz+4LbbSeRFiWFbJhlEgJ1vrg2iWAXx18ZkYWI2AkoQV+kPoj+SBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-30T14:11:23.380794Z","bundle_sha256":"95ce83beac6040f1f1430ecdba07532d86f48481275acae41ebe11512541baa7"}}