{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:CGNJB56VEMX6U6UUYY6L6PO4YT","short_pith_number":"pith:CGNJB56V","schema_version":"1.0","canonical_sha256":"119a90f7d5232fea7a94c63cbf3ddcc4e6005455c14afd469dbc62a1ac5ba069","source":{"kind":"arxiv","id":"1808.05380","version":1},"attestation_state":"computed","paper":{"title":"Egocentric Gesture Recognition for Head-Mounted AR devices","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Aljosa Smolic, Jan Ondrej, Tejo Chalasani","submitted_at":"2018-08-16T09:00:56Z","abstract_excerpt":"Natural interaction with virtual objects in AR/VR environments makes for a smooth user experience. Gestures are a natural extension from real world to augmented space to achieve these interactions. Finding discriminating spatio-temporal features relevant to gestures and hands in ego-view is the primary challenge for recognising egocentric gestures. In this work we propose a data driven end-to-end deep learning approach to address the problem of egocentric gesture recognition, which combines an ego-hand encoder network to find ego-hand features, and a recurrent neural network to discern tempora"},"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":"1808.05380","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-16T09:00:56Z","cross_cats_sorted":[],"title_canon_sha256":"2250d409389760dedd3b4b577e8df549cb38d434d6bd6fbf0aae136551daa145","abstract_canon_sha256":"5044dd4198db4edb2d113395efa722b6d70cbd6f2a063941aa9c506a408f8d86"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:07:57.278574Z","signature_b64":"MssvvkKR/6ctYT7D84WleKim0aRFa8n7VmcXo+wnn9AQkjmtFf2mprZgc/Om5XnzxvOHDlaKLP3bdANtrfX3DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"119a90f7d5232fea7a94c63cbf3ddcc4e6005455c14afd469dbc62a1ac5ba069","last_reissued_at":"2026-05-18T00:07:57.277852Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:07:57.277852Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Egocentric Gesture Recognition for Head-Mounted AR devices","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Aljosa Smolic, Jan Ondrej, Tejo Chalasani","submitted_at":"2018-08-16T09:00:56Z","abstract_excerpt":"Natural interaction with virtual objects in AR/VR environments makes for a smooth user experience. Gestures are a natural extension from real world to augmented space to achieve these interactions. Finding discriminating spatio-temporal features relevant to gestures and hands in ego-view is the primary challenge for recognising egocentric gestures. In this work we propose a data driven end-to-end deep learning approach to address the problem of egocentric gesture recognition, which combines an ego-hand encoder network to find ego-hand features, and a recurrent neural network to discern tempora"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.05380","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1808.05380","created_at":"2026-05-18T00:07:57.277965+00:00"},{"alias_kind":"arxiv_version","alias_value":"1808.05380v1","created_at":"2026-05-18T00:07:57.277965+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.05380","created_at":"2026-05-18T00:07:57.277965+00:00"},{"alias_kind":"pith_short_12","alias_value":"CGNJB56VEMX6","created_at":"2026-05-18T12:32:16.446611+00:00"},{"alias_kind":"pith_short_16","alias_value":"CGNJB56VEMX6U6UU","created_at":"2026-05-18T12:32:16.446611+00:00"},{"alias_kind":"pith_short_8","alias_value":"CGNJB56V","created_at":"2026-05-18T12:32:16.446611+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/CGNJB56VEMX6U6UUYY6L6PO4YT","json":"https://pith.science/pith/CGNJB56VEMX6U6UUYY6L6PO4YT.json","graph_json":"https://pith.science/api/pith-number/CGNJB56VEMX6U6UUYY6L6PO4YT/graph.json","events_json":"https://pith.science/api/pith-number/CGNJB56VEMX6U6UUYY6L6PO4YT/events.json","paper":"https://pith.science/paper/CGNJB56V"},"agent_actions":{"view_html":"https://pith.science/pith/CGNJB56VEMX6U6UUYY6L6PO4YT","download_json":"https://pith.science/pith/CGNJB56VEMX6U6UUYY6L6PO4YT.json","view_paper":"https://pith.science/paper/CGNJB56V","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1808.05380&json=true","fetch_graph":"https://pith.science/api/pith-number/CGNJB56VEMX6U6UUYY6L6PO4YT/graph.json","fetch_events":"https://pith.science/api/pith-number/CGNJB56VEMX6U6UUYY6L6PO4YT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CGNJB56VEMX6U6UUYY6L6PO4YT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CGNJB56VEMX6U6UUYY6L6PO4YT/action/storage_attestation","attest_author":"https://pith.science/pith/CGNJB56VEMX6U6UUYY6L6PO4YT/action/author_attestation","sign_citation":"https://pith.science/pith/CGNJB56VEMX6U6UUYY6L6PO4YT/action/citation_signature","submit_replication":"https://pith.science/pith/CGNJB56VEMX6U6UUYY6L6PO4YT/action/replication_record"}},"created_at":"2026-05-18T00:07:57.277965+00:00","updated_at":"2026-05-18T00:07:57.277965+00:00"}