{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:CQA2GWLJQB3A7CFMFXL53ISBFR","short_pith_number":"pith:CQA2GWLJ","schema_version":"1.0","canonical_sha256":"1401a3596980760f88ac2dd7dda2412c7c7e66c88c3d81ff09d89156bb33a4ac","source":{"kind":"arxiv","id":"2205.11232","version":2},"attestation_state":"computed","paper":{"title":"Deep Neural Network approaches for Analysing Videos of Music Performances","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG","cs.MM"],"primary_cat":"cs.CV","authors_text":"Federico Visi, Foteini Simistira Liwicki, Killian Murphy, Marcus Liwicki, Prakash Chandra Chhipa, Richa Upadhyay, Stefan \\\"Ostersj\\\"o","submitted_at":"2022-05-05T09:04:04Z","abstract_excerpt":"This paper presents a framework to automate the labelling process for gestures in musical performance videos with a 3D Convolutional Neural Network (CNN). While this idea was proposed in a previous study, this paper introduces several novelties: (i) Presents a novel method to overcome the class imbalance challenge and make learning possible for co-existent gestures by batch balancing approach and spatial-temporal representations of gestures. (ii) Performs a detailed study on 7 and 18 categories of gestures generated during the performance (guitar play) of musical pieces that have been video-re"},"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":"2205.11232","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-05-05T09:04:04Z","cross_cats_sorted":["cs.AI","cs.LG","cs.MM"],"title_canon_sha256":"b30e0fcfd3e2a08530b2ad74e784f857476eeff8740b8937cb2d29cf7387ff70","abstract_canon_sha256":"de09c58797b1158f3d971b99a21e8b41d3ec1906f401161d329e76a5e9a24504"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:26:04.906328Z","signature_b64":"nYiu1kpIaCUWPkjyXOXMNn8k9X2GySTkTdo0FJSTxpoS298ncpl74nisBIdUw23+db5Y/v6JtT+H7UmYHGKhAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1401a3596980760f88ac2dd7dda2412c7c7e66c88c3d81ff09d89156bb33a4ac","last_reissued_at":"2026-07-05T04:26:04.905925Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:26:04.905925Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Deep Neural Network approaches for Analysing Videos of Music Performances","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG","cs.MM"],"primary_cat":"cs.CV","authors_text":"Federico Visi, Foteini Simistira Liwicki, Killian Murphy, Marcus Liwicki, Prakash Chandra Chhipa, Richa Upadhyay, Stefan \\\"Ostersj\\\"o","submitted_at":"2022-05-05T09:04:04Z","abstract_excerpt":"This paper presents a framework to automate the labelling process for gestures in musical performance videos with a 3D Convolutional Neural Network (CNN). While this idea was proposed in a previous study, this paper introduces several novelties: (i) Presents a novel method to overcome the class imbalance challenge and make learning possible for co-existent gestures by batch balancing approach and spatial-temporal representations of gestures. (ii) Performs a detailed study on 7 and 18 categories of gestures generated during the performance (guitar play) of musical pieces that have been video-re"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.11232","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2205.11232/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2205.11232","created_at":"2026-07-05T04:26:04.905977+00:00"},{"alias_kind":"arxiv_version","alias_value":"2205.11232v2","created_at":"2026-07-05T04:26:04.905977+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.11232","created_at":"2026-07-05T04:26:04.905977+00:00"},{"alias_kind":"pith_short_12","alias_value":"CQA2GWLJQB3A","created_at":"2026-07-05T04:26:04.905977+00:00"},{"alias_kind":"pith_short_16","alias_value":"CQA2GWLJQB3A7CFM","created_at":"2026-07-05T04:26:04.905977+00:00"},{"alias_kind":"pith_short_8","alias_value":"CQA2GWLJ","created_at":"2026-07-05T04:26:04.905977+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/CQA2GWLJQB3A7CFMFXL53ISBFR","json":"https://pith.science/pith/CQA2GWLJQB3A7CFMFXL53ISBFR.json","graph_json":"https://pith.science/api/pith-number/CQA2GWLJQB3A7CFMFXL53ISBFR/graph.json","events_json":"https://pith.science/api/pith-number/CQA2GWLJQB3A7CFMFXL53ISBFR/events.json","paper":"https://pith.science/paper/CQA2GWLJ"},"agent_actions":{"view_html":"https://pith.science/pith/CQA2GWLJQB3A7CFMFXL53ISBFR","download_json":"https://pith.science/pith/CQA2GWLJQB3A7CFMFXL53ISBFR.json","view_paper":"https://pith.science/paper/CQA2GWLJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2205.11232&json=true","fetch_graph":"https://pith.science/api/pith-number/CQA2GWLJQB3A7CFMFXL53ISBFR/graph.json","fetch_events":"https://pith.science/api/pith-number/CQA2GWLJQB3A7CFMFXL53ISBFR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CQA2GWLJQB3A7CFMFXL53ISBFR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CQA2GWLJQB3A7CFMFXL53ISBFR/action/storage_attestation","attest_author":"https://pith.science/pith/CQA2GWLJQB3A7CFMFXL53ISBFR/action/author_attestation","sign_citation":"https://pith.science/pith/CQA2GWLJQB3A7CFMFXL53ISBFR/action/citation_signature","submit_replication":"https://pith.science/pith/CQA2GWLJQB3A7CFMFXL53ISBFR/action/replication_record"}},"created_at":"2026-07-05T04:26:04.905977+00:00","updated_at":"2026-07-05T04:26:04.905977+00:00"}