{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:MEVJ3QQ3JQLTGS5AEV2RO2CLLS","short_pith_number":"pith:MEVJ3QQ3","canonical_record":{"source":{"id":"1907.09382","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-22T15:52:21Z","cross_cats_sorted":[],"title_canon_sha256":"6e064b21e5b7a6ac94e42105ad2daff4cd45ee6f678f7f35ebff69bfdd45eac2","abstract_canon_sha256":"124ce54bc0328e73d5ad9e6c6fd71074540b12e4f0f8f7b7f52997593ed03312"},"schema_version":"1.0"},"canonical_sha256":"612a9dc21b4c17334ba0257517684b5cb36817ef563b465aa7f7e8067f6913ab","source":{"kind":"arxiv","id":"1907.09382","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.09382","created_at":"2026-07-05T03:38:57Z"},{"alias_kind":"arxiv_version","alias_value":"1907.09382v3","created_at":"2026-07-05T03:38:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.09382","created_at":"2026-07-05T03:38:57Z"},{"alias_kind":"pith_short_12","alias_value":"MEVJ3QQ3JQLT","created_at":"2026-07-05T03:38:57Z"},{"alias_kind":"pith_short_16","alias_value":"MEVJ3QQ3JQLTGS5A","created_at":"2026-07-05T03:38:57Z"},{"alias_kind":"pith_short_8","alias_value":"MEVJ3QQ3","created_at":"2026-07-05T03:38:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:MEVJ3QQ3JQLTGS5AEV2RO2CLLS","target":"record","payload":{"canonical_record":{"source":{"id":"1907.09382","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-22T15:52:21Z","cross_cats_sorted":[],"title_canon_sha256":"6e064b21e5b7a6ac94e42105ad2daff4cd45ee6f678f7f35ebff69bfdd45eac2","abstract_canon_sha256":"124ce54bc0328e73d5ad9e6c6fd71074540b12e4f0f8f7b7f52997593ed03312"},"schema_version":"1.0"},"canonical_sha256":"612a9dc21b4c17334ba0257517684b5cb36817ef563b465aa7f7e8067f6913ab","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:38:57.554865Z","signature_b64":"3Ieq/532G1AxQNRBy9xR/h5SNmWC0cXATjuu7afjLsa4o3qdMUY9SU3Z3T+Z1n0rd3GTo0bZEP8x6PbvuJOcAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"612a9dc21b4c17334ba0257517684b5cb36817ef563b465aa7f7e8067f6913ab","last_reissued_at":"2026-07-05T03:38:57.554375Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:38:57.554375Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1907.09382","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":"2026-07-05T03:38:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VX8DViq+oEwttgVALb452Xc6ogalzRDafpwr5/doh6/veTmwfn1ORa/JYEcYPXz5sAWtWKmB/pHPaCIxt0zMCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-10T00:38:20.293998Z"},"content_sha256":"e498a26970b32f2d36d17241281827b5a2b4f2add7d8a2d9c27490cb784d0e91","schema_version":"1.0","event_id":"sha256:e498a26970b32f2d36d17241281827b5a2b4f2add7d8a2d9c27490cb784d0e91"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:MEVJ3QQ3JQLTGS5AEV2RO2CLLS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Domain-Specific Priors and Meta Learning for Few-Shot First-Person Action Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bugra Tekin, Federica Bogo, Federico Tombari, Harpreet Sawhney, Huseyin Coskun, Nassir Navab, Zeeshan Zia","submitted_at":"2019-07-22T15:52:21Z","abstract_excerpt":"The lack of large-scale real datasets with annotations makes transfer learning a necessity for video activity understanding. We aim to develop an effective method for few-shot transfer learning for first-person action classification. We leverage independently trained local visual cues to learn representations that can be transferred from a source domain, which provides primitive action labels, to a different target domain using only a handful of examples. Visual cues we employ include object-object interactions, hand grasps and motion within regions that are a function of hand locations. We em"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.09382","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1907.09382/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":"2026-07-05T03:38:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"d9LtxQslKD+otV6tus4WAGYiCJ461lSMCkffBWzoFqigTYMNiYQsw+w4lc5weUKJyydS9VFSP5xFdHtwQ3QFCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-10T00:38:20.294407Z"},"content_sha256":"316a9db8e573994c4b6dc82432628e34c2aa28ac0f0b0bd07f71b5d9336f92ec","schema_version":"1.0","event_id":"sha256:316a9db8e573994c4b6dc82432628e34c2aa28ac0f0b0bd07f71b5d9336f92ec"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MEVJ3QQ3JQLTGS5AEV2RO2CLLS/bundle.json","state_url":"https://pith.science/pith/MEVJ3QQ3JQLTGS5AEV2RO2CLLS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MEVJ3QQ3JQLTGS5AEV2RO2CLLS/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":"2026-07-10T00:38:20Z","links":{"resolver":"https://pith.science/pith/MEVJ3QQ3JQLTGS5AEV2RO2CLLS","bundle":"https://pith.science/pith/MEVJ3QQ3JQLTGS5AEV2RO2CLLS/bundle.json","state":"https://pith.science/pith/MEVJ3QQ3JQLTGS5AEV2RO2CLLS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MEVJ3QQ3JQLTGS5AEV2RO2CLLS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:MEVJ3QQ3JQLTGS5AEV2RO2CLLS","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":"124ce54bc0328e73d5ad9e6c6fd71074540b12e4f0f8f7b7f52997593ed03312","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-22T15:52:21Z","title_canon_sha256":"6e064b21e5b7a6ac94e42105ad2daff4cd45ee6f678f7f35ebff69bfdd45eac2"},"schema_version":"1.0","source":{"id":"1907.09382","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.09382","created_at":"2026-07-05T03:38:57Z"},{"alias_kind":"arxiv_version","alias_value":"1907.09382v3","created_at":"2026-07-05T03:38:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.09382","created_at":"2026-07-05T03:38:57Z"},{"alias_kind":"pith_short_12","alias_value":"MEVJ3QQ3JQLT","created_at":"2026-07-05T03:38:57Z"},{"alias_kind":"pith_short_16","alias_value":"MEVJ3QQ3JQLTGS5A","created_at":"2026-07-05T03:38:57Z"},{"alias_kind":"pith_short_8","alias_value":"MEVJ3QQ3","created_at":"2026-07-05T03:38:57Z"}],"graph_snapshots":[{"event_id":"sha256:316a9db8e573994c4b6dc82432628e34c2aa28ac0f0b0bd07f71b5d9336f92ec","target":"graph","created_at":"2026-07-05T03:38:57Z","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/1907.09382/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The lack of large-scale real datasets with annotations makes transfer learning a necessity for video activity understanding. We aim to develop an effective method for few-shot transfer learning for first-person action classification. We leverage independently trained local visual cues to learn representations that can be transferred from a source domain, which provides primitive action labels, to a different target domain using only a handful of examples. Visual cues we employ include object-object interactions, hand grasps and motion within regions that are a function of hand locations. We em","authors_text":"Bugra Tekin, Federica Bogo, Federico Tombari, Harpreet Sawhney, Huseyin Coskun, Nassir Navab, Zeeshan Zia","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-22T15:52:21Z","title":"Domain-Specific Priors and Meta Learning for Few-Shot First-Person Action Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.09382","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:e498a26970b32f2d36d17241281827b5a2b4f2add7d8a2d9c27490cb784d0e91","target":"record","created_at":"2026-07-05T03:38:57Z","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":"124ce54bc0328e73d5ad9e6c6fd71074540b12e4f0f8f7b7f52997593ed03312","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-22T15:52:21Z","title_canon_sha256":"6e064b21e5b7a6ac94e42105ad2daff4cd45ee6f678f7f35ebff69bfdd45eac2"},"schema_version":"1.0","source":{"id":"1907.09382","kind":"arxiv","version":3}},"canonical_sha256":"612a9dc21b4c17334ba0257517684b5cb36817ef563b465aa7f7e8067f6913ab","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"612a9dc21b4c17334ba0257517684b5cb36817ef563b465aa7f7e8067f6913ab","first_computed_at":"2026-07-05T03:38:57.554375Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:38:57.554375Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3Ieq/532G1AxQNRBy9xR/h5SNmWC0cXATjuu7afjLsa4o3qdMUY9SU3Z3T+Z1n0rd3GTo0bZEP8x6PbvuJOcAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T03:38:57.554865Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.09382","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e498a26970b32f2d36d17241281827b5a2b4f2add7d8a2d9c27490cb784d0e91","sha256:316a9db8e573994c4b6dc82432628e34c2aa28ac0f0b0bd07f71b5d9336f92ec"],"state_sha256":"6a4c7d4f229268aef230634a529f2741d000e4c576f5192b1abef9bff41d2cce"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"F+IAZCiBrCZycYFgnsRFy10SWbtnD7CNdvHKkvMMkJMEJq5hxxrp8TvdLR8MaS/XUVwT+8lG6OzPpHuvSliJDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-10T00:38:20.296774Z","bundle_sha256":"f4918183a92da8dc1f898800f886af3762df3620294a0c90e58c2df503b0a3b7"}}