{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:CZGDOVYJRMVAT2D7GUXBSRFYCZ","short_pith_number":"pith:CZGDOVYJ","canonical_record":{"source":{"id":"2008.01003","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-08-03T16:41:19Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"cbfc047dea93f5983b40793503e4705a3e57612513b63f6b41539473ea5d4c3d","abstract_canon_sha256":"8aa31428f6e0677c91cb8bc2737febcb648643ce7eee371f7cc45ce9f890eb6f"},"schema_version":"1.0"},"canonical_sha256":"164c3757098b2a09e87f352e1944b81642fcffa1501562077eb4e5c049233cbe","source":{"kind":"arxiv","id":"2008.01003","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2008.01003","created_at":"2026-07-05T02:18:16Z"},{"alias_kind":"arxiv_version","alias_value":"2008.01003v2","created_at":"2026-07-05T02:18:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2008.01003","created_at":"2026-07-05T02:18:16Z"},{"alias_kind":"pith_short_12","alias_value":"CZGDOVYJRMVA","created_at":"2026-07-05T02:18:16Z"},{"alias_kind":"pith_short_16","alias_value":"CZGDOVYJRMVAT2D7","created_at":"2026-07-05T02:18:16Z"},{"alias_kind":"pith_short_8","alias_value":"CZGDOVYJ","created_at":"2026-07-05T02:18:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:CZGDOVYJRMVAT2D7GUXBSRFYCZ","target":"record","payload":{"canonical_record":{"source":{"id":"2008.01003","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-08-03T16:41:19Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"cbfc047dea93f5983b40793503e4705a3e57612513b63f6b41539473ea5d4c3d","abstract_canon_sha256":"8aa31428f6e0677c91cb8bc2737febcb648643ce7eee371f7cc45ce9f890eb6f"},"schema_version":"1.0"},"canonical_sha256":"164c3757098b2a09e87f352e1944b81642fcffa1501562077eb4e5c049233cbe","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:18:16.863640Z","signature_b64":"i6NHxdgPa/E8x3C3jw0xeUaJBvMRYbj0IVTziSeOfncbdLdjEdVEd42EIUH1YCI4lv0Fxc/6+qdxI0wuh2XqBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"164c3757098b2a09e87f352e1944b81642fcffa1501562077eb4e5c049233cbe","last_reissued_at":"2026-07-05T02:18:16.863231Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:18:16.863231Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2008.01003","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:18:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6oeBD60hyYd3lpJ4ykvuMkQTeCr4O8lWO/GtsLGmdPENLhRDeTw1RTewPIADjo0BkmAuSm+VTNOlsuG+ERtZBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T02:01:59.365918Z"},"content_sha256":"1e1c339a0bf270b564a590eed9f7b0b05cc05ccf8271f601d9965444d5e723b1","schema_version":"1.0","event_id":"sha256:1e1c339a0bf270b564a590eed9f7b0b05cc05ccf8271f601d9965444d5e723b1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:CZGDOVYJRMVAT2D7GUXBSRFYCZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Teacher-Student Training and Triplet Loss for Facial Expression Recognition under Occlusion","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Mariana-Iuliana Georgescu, Radu Tudor Ionescu","submitted_at":"2020-08-03T16:41:19Z","abstract_excerpt":"In this paper, we study the task of facial expression recognition under strong occlusion. We are particularly interested in cases where 50% of the face is occluded, e.g. when the subject wears a Virtual Reality (VR) headset. While previous studies show that pre-training convolutional neural networks (CNNs) on fully-visible (non-occluded) faces improves the accuracy, we propose to employ knowledge distillation to achieve further improvements. First of all, we employ the classic teacher-student training strategy, in which the teacher is a CNN trained on fully-visible faces and the student is a C"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2008.01003","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/2008.01003/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":"2026-07-05T02:18:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"X75RiI0yKKsHMmAxiHE9sYjOM0WWEoGL59b7RCWOkYNBpFo3PflDlHpZ3gs8roLoyboATkjA6XmlfSrk2dMoAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T02:01:59.366298Z"},"content_sha256":"b07b960460866ce632e553ead108c5bca65ab97a6ca082a1937e89c9da7496f7","schema_version":"1.0","event_id":"sha256:b07b960460866ce632e553ead108c5bca65ab97a6ca082a1937e89c9da7496f7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CZGDOVYJRMVAT2D7GUXBSRFYCZ/bundle.json","state_url":"https://pith.science/pith/CZGDOVYJRMVAT2D7GUXBSRFYCZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CZGDOVYJRMVAT2D7GUXBSRFYCZ/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":"2026-07-09T02:01:59Z","links":{"resolver":"https://pith.science/pith/CZGDOVYJRMVAT2D7GUXBSRFYCZ","bundle":"https://pith.science/pith/CZGDOVYJRMVAT2D7GUXBSRFYCZ/bundle.json","state":"https://pith.science/pith/CZGDOVYJRMVAT2D7GUXBSRFYCZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CZGDOVYJRMVAT2D7GUXBSRFYCZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:CZGDOVYJRMVAT2D7GUXBSRFYCZ","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":"8aa31428f6e0677c91cb8bc2737febcb648643ce7eee371f7cc45ce9f890eb6f","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-08-03T16:41:19Z","title_canon_sha256":"cbfc047dea93f5983b40793503e4705a3e57612513b63f6b41539473ea5d4c3d"},"schema_version":"1.0","source":{"id":"2008.01003","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2008.01003","created_at":"2026-07-05T02:18:16Z"},{"alias_kind":"arxiv_version","alias_value":"2008.01003v2","created_at":"2026-07-05T02:18:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2008.01003","created_at":"2026-07-05T02:18:16Z"},{"alias_kind":"pith_short_12","alias_value":"CZGDOVYJRMVA","created_at":"2026-07-05T02:18:16Z"},{"alias_kind":"pith_short_16","alias_value":"CZGDOVYJRMVAT2D7","created_at":"2026-07-05T02:18:16Z"},{"alias_kind":"pith_short_8","alias_value":"CZGDOVYJ","created_at":"2026-07-05T02:18:16Z"}],"graph_snapshots":[{"event_id":"sha256:b07b960460866ce632e553ead108c5bca65ab97a6ca082a1937e89c9da7496f7","target":"graph","created_at":"2026-07-05T02:18:16Z","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/2008.01003/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we study the task of facial expression recognition under strong occlusion. We are particularly interested in cases where 50% of the face is occluded, e.g. when the subject wears a Virtual Reality (VR) headset. While previous studies show that pre-training convolutional neural networks (CNNs) on fully-visible (non-occluded) faces improves the accuracy, we propose to employ knowledge distillation to achieve further improvements. First of all, we employ the classic teacher-student training strategy, in which the teacher is a CNN trained on fully-visible faces and the student is a C","authors_text":"Mariana-Iuliana Georgescu, Radu Tudor Ionescu","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-08-03T16:41:19Z","title":"Teacher-Student Training and Triplet Loss for Facial Expression Recognition under Occlusion"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2008.01003","kind":"arxiv","version":2},"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":"sha256:1e1c339a0bf270b564a590eed9f7b0b05cc05ccf8271f601d9965444d5e723b1","target":"record","created_at":"2026-07-05T02:18:16Z","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":"8aa31428f6e0677c91cb8bc2737febcb648643ce7eee371f7cc45ce9f890eb6f","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-08-03T16:41:19Z","title_canon_sha256":"cbfc047dea93f5983b40793503e4705a3e57612513b63f6b41539473ea5d4c3d"},"schema_version":"1.0","source":{"id":"2008.01003","kind":"arxiv","version":2}},"canonical_sha256":"164c3757098b2a09e87f352e1944b81642fcffa1501562077eb4e5c049233cbe","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"164c3757098b2a09e87f352e1944b81642fcffa1501562077eb4e5c049233cbe","first_computed_at":"2026-07-05T02:18:16.863231Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:18:16.863231Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"i6NHxdgPa/E8x3C3jw0xeUaJBvMRYbj0IVTziSeOfncbdLdjEdVEd42EIUH1YCI4lv0Fxc/6+qdxI0wuh2XqBg==","signature_status":"signed_v1","signed_at":"2026-07-05T02:18:16.863640Z","signed_message":"canonical_sha256_bytes"},"source_id":"2008.01003","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1e1c339a0bf270b564a590eed9f7b0b05cc05ccf8271f601d9965444d5e723b1","sha256:b07b960460866ce632e553ead108c5bca65ab97a6ca082a1937e89c9da7496f7"],"state_sha256":"b263b0a39a0f2b501b417416d2f3d3d7d56c787f6b5381036838b45d43bc085f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RKn6M3su4/zOBbsDrwBF0qj8LeQ+35vPishnoBmSGDTmk2ZfCXumJd+PNw2AGebKvnjE6eBawTnA2D6OGqdFCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-09T02:01:59.368365Z","bundle_sha256":"0e31612b813f5a9eef476a677c9fec1ca66d1cc8d72b6fe386fabdca7a54c5c9"}}