{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:2NHK3G5RT76KV4VHCTSELV5WYO","short_pith_number":"pith:2NHK3G5R","schema_version":"1.0","canonical_sha256":"d34ead9bb19ffcaaf2a714e445d7b6c38e79eab34683014e03d2b7f1dc58bb8b","source":{"kind":"arxiv","id":"1508.06073","version":2},"attestation_state":"computed","paper":{"title":"Cooking in the kitchen: Recognizing and Segmenting Human Activities in Videos","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hilde Kuehne, Juergen Gall, Thomas Serre","submitted_at":"2015-08-25T08:59:46Z","abstract_excerpt":"As research on action recognition matures, the focus is shifting away from categorizing basic task-oriented actions using hand-segmented video datasets to understanding complex goal-oriented daily human activities in real-world settings. Temporally structured models would seem obvious to tackle this set of problems, but so far, cases where these models have outperformed simpler unstructured bag-of-word types of models are scarce. With the increasing availability of large human activity datasets, combined with the development of novel feature coding techniques that yield more compact representa"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1508.06073","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-08-25T08:59:46Z","cross_cats_sorted":[],"title_canon_sha256":"18b3aee9e03404f65fbf12bc382c670b340dc12b0419d10a89052772dc325601","abstract_canon_sha256":"8a77ec3325dddc9e06d793203cf2944e675e3af4e3e4592bcaf71b6d88de4582"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:18:57.283629Z","signature_b64":"FxRqRudPp+OlEiwyc9P87tvBJKEneTj4WJ4IpMrDJcfokDhpSL7KFlnO8hhE1J0qRPncV/dOmbs1XXseI28+BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d34ead9bb19ffcaaf2a714e445d7b6c38e79eab34683014e03d2b7f1dc58bb8b","last_reissued_at":"2026-05-18T01:18:57.283202Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:18:57.283202Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Cooking in the kitchen: Recognizing and Segmenting Human Activities in Videos","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hilde Kuehne, Juergen Gall, Thomas Serre","submitted_at":"2015-08-25T08:59:46Z","abstract_excerpt":"As research on action recognition matures, the focus is shifting away from categorizing basic task-oriented actions using hand-segmented video datasets to understanding complex goal-oriented daily human activities in real-world settings. Temporally structured models would seem obvious to tackle this set of problems, but so far, cases where these models have outperformed simpler unstructured bag-of-word types of models are scarce. With the increasing availability of large human activity datasets, combined with the development of novel feature coding techniques that yield more compact representa"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1508.06073","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1508.06073","created_at":"2026-05-18T01:18:57.283267+00:00"},{"alias_kind":"arxiv_version","alias_value":"1508.06073v2","created_at":"2026-05-18T01:18:57.283267+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1508.06073","created_at":"2026-05-18T01:18:57.283267+00:00"},{"alias_kind":"pith_short_12","alias_value":"2NHK3G5RT76K","created_at":"2026-05-18T12:29:02.477457+00:00"},{"alias_kind":"pith_short_16","alias_value":"2NHK3G5RT76KV4VH","created_at":"2026-05-18T12:29:02.477457+00:00"},{"alias_kind":"pith_short_8","alias_value":"2NHK3G5R","created_at":"2026-05-18T12:29:02.477457+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/2NHK3G5RT76KV4VHCTSELV5WYO","json":"https://pith.science/pith/2NHK3G5RT76KV4VHCTSELV5WYO.json","graph_json":"https://pith.science/api/pith-number/2NHK3G5RT76KV4VHCTSELV5WYO/graph.json","events_json":"https://pith.science/api/pith-number/2NHK3G5RT76KV4VHCTSELV5WYO/events.json","paper":"https://pith.science/paper/2NHK3G5R"},"agent_actions":{"view_html":"https://pith.science/pith/2NHK3G5RT76KV4VHCTSELV5WYO","download_json":"https://pith.science/pith/2NHK3G5RT76KV4VHCTSELV5WYO.json","view_paper":"https://pith.science/paper/2NHK3G5R","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1508.06073&json=true","fetch_graph":"https://pith.science/api/pith-number/2NHK3G5RT76KV4VHCTSELV5WYO/graph.json","fetch_events":"https://pith.science/api/pith-number/2NHK3G5RT76KV4VHCTSELV5WYO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2NHK3G5RT76KV4VHCTSELV5WYO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2NHK3G5RT76KV4VHCTSELV5WYO/action/storage_attestation","attest_author":"https://pith.science/pith/2NHK3G5RT76KV4VHCTSELV5WYO/action/author_attestation","sign_citation":"https://pith.science/pith/2NHK3G5RT76KV4VHCTSELV5WYO/action/citation_signature","submit_replication":"https://pith.science/pith/2NHK3G5RT76KV4VHCTSELV5WYO/action/replication_record"}},"created_at":"2026-05-18T01:18:57.283267+00:00","updated_at":"2026-05-18T01:18:57.283267+00:00"}