{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:VVA7GLZA3AWVR24M25AEJSBM26","short_pith_number":"pith:VVA7GLZA","schema_version":"1.0","canonical_sha256":"ad41f32f20d82d58eb8cd74044c82cd79919bd1d02e4a3b0f498e2bbdf12a92b","source":{"kind":"arxiv","id":"1502.06648","version":2},"attestation_state":"computed","paper":{"title":"Recognizing Fine-Grained and Composite Activities using Hand-Centric Features and Script Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Anna Rohrbach, Bernt Schiele, Manfred Pinkal, Marcus Rohrbach, Michaela Regneri, Mykhaylo Andriluka, Sikandar Amin","submitted_at":"2015-02-23T22:48:17Z","abstract_excerpt":"Activity recognition has shown impressive progress in recent years. However, the challenges of detecting fine-grained activities and understanding how they are combined into composite activities have been largely overlooked. In this work we approach both tasks and present a dataset which provides detailed annotations to address them. The first challenge is to detect fine-grained activities, which are defined by low inter-class variability and are typically characterized by fine-grained body motions. We explore how human pose and hands can help to approach this challenge by comparing two pose-b"},"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":"1502.06648","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-02-23T22:48:17Z","cross_cats_sorted":[],"title_canon_sha256":"8ee257ce462d3755f919287df1d3bedc5187a38917201a39c98116e52e4c8981","abstract_canon_sha256":"122b3d23a35922d310b5fa5c22c4e67625ef5fb8fddc49f58512e15feb03c0f2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:30:08.089433Z","signature_b64":"c8Q1jbGPnhkBVjA/u9L6QAHBgJTyseB9TORbNEAdZTio66aF2ln3h31wYWek3YwdGLKh9GsE66m7ZDQbu6GwDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ad41f32f20d82d58eb8cd74044c82cd79919bd1d02e4a3b0f498e2bbdf12a92b","last_reissued_at":"2026-05-18T01:30:08.088922Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:30:08.088922Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Recognizing Fine-Grained and Composite Activities using Hand-Centric Features and Script Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Anna Rohrbach, Bernt Schiele, Manfred Pinkal, Marcus Rohrbach, Michaela Regneri, Mykhaylo Andriluka, Sikandar Amin","submitted_at":"2015-02-23T22:48:17Z","abstract_excerpt":"Activity recognition has shown impressive progress in recent years. However, the challenges of detecting fine-grained activities and understanding how they are combined into composite activities have been largely overlooked. In this work we approach both tasks and present a dataset which provides detailed annotations to address them. The first challenge is to detect fine-grained activities, which are defined by low inter-class variability and are typically characterized by fine-grained body motions. We explore how human pose and hands can help to approach this challenge by comparing two pose-b"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1502.06648","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":"1502.06648","created_at":"2026-05-18T01:30:08.089000+00:00"},{"alias_kind":"arxiv_version","alias_value":"1502.06648v2","created_at":"2026-05-18T01:30:08.089000+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1502.06648","created_at":"2026-05-18T01:30:08.089000+00:00"},{"alias_kind":"pith_short_12","alias_value":"VVA7GLZA3AWV","created_at":"2026-05-18T12:29:47.479230+00:00"},{"alias_kind":"pith_short_16","alias_value":"VVA7GLZA3AWVR24M","created_at":"2026-05-18T12:29:47.479230+00:00"},{"alias_kind":"pith_short_8","alias_value":"VVA7GLZA","created_at":"2026-05-18T12:29:47.479230+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/VVA7GLZA3AWVR24M25AEJSBM26","json":"https://pith.science/pith/VVA7GLZA3AWVR24M25AEJSBM26.json","graph_json":"https://pith.science/api/pith-number/VVA7GLZA3AWVR24M25AEJSBM26/graph.json","events_json":"https://pith.science/api/pith-number/VVA7GLZA3AWVR24M25AEJSBM26/events.json","paper":"https://pith.science/paper/VVA7GLZA"},"agent_actions":{"view_html":"https://pith.science/pith/VVA7GLZA3AWVR24M25AEJSBM26","download_json":"https://pith.science/pith/VVA7GLZA3AWVR24M25AEJSBM26.json","view_paper":"https://pith.science/paper/VVA7GLZA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1502.06648&json=true","fetch_graph":"https://pith.science/api/pith-number/VVA7GLZA3AWVR24M25AEJSBM26/graph.json","fetch_events":"https://pith.science/api/pith-number/VVA7GLZA3AWVR24M25AEJSBM26/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VVA7GLZA3AWVR24M25AEJSBM26/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VVA7GLZA3AWVR24M25AEJSBM26/action/storage_attestation","attest_author":"https://pith.science/pith/VVA7GLZA3AWVR24M25AEJSBM26/action/author_attestation","sign_citation":"https://pith.science/pith/VVA7GLZA3AWVR24M25AEJSBM26/action/citation_signature","submit_replication":"https://pith.science/pith/VVA7GLZA3AWVR24M25AEJSBM26/action/replication_record"}},"created_at":"2026-05-18T01:30:08.089000+00:00","updated_at":"2026-05-18T01:30:08.089000+00:00"}