{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:QL3NDCYNIQUEUQS6E42HOATCCW","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":"2487b02ba752a1f7c801eed6223fa023d377b820cc9f66a5a7eab1bfd7381908","cross_cats_sorted":["cs.AI","cs.CV","cs.MM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2022-05-06T16:31:57Z","title_canon_sha256":"6dd34d217cf660c2810fe977487447580dafa1d2e52a313c20660d049b4a15cf"},"schema_version":"1.0","source":{"id":"2205.03409","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.03409","created_at":"2026-07-05T04:21:13Z"},{"alias_kind":"arxiv_version","alias_value":"2205.03409v1","created_at":"2026-07-05T04:21:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.03409","created_at":"2026-07-05T04:21:13Z"},{"alias_kind":"pith_short_12","alias_value":"QL3NDCYNIQUE","created_at":"2026-07-05T04:21:13Z"},{"alias_kind":"pith_short_16","alias_value":"QL3NDCYNIQUEUQS6","created_at":"2026-07-05T04:21:13Z"},{"alias_kind":"pith_short_8","alias_value":"QL3NDCYN","created_at":"2026-07-05T04:21:13Z"}],"graph_snapshots":[{"event_id":"sha256:cba48bbf985164bee12ad7acf8e70216ef9e30e4bff459d15cb0c66a0fdbae8a","target":"graph","created_at":"2026-07-05T04:21:13Z","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/2205.03409/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Most of the existing video face super-resolution (VFSR) methods are trained and evaluated on VoxCeleb1, which is designed specifically for speaker identification and the frames in this dataset are of low quality. As a consequence, the VFSR models trained on this dataset can not output visual-pleasing results. In this paper, we develop an automatic and scalable pipeline to collect a high-quality video face dataset (VFHQ), which contains over $16,000$ high-fidelity clips of diverse interview scenarios. To verify the necessity of VFHQ, we further conduct experiments and demonstrate that VFSR mode","authors_text":"Chao Dong, Honglun Zhang, Liangbin Xie. Xintao Wang, Ying Shan","cross_cats":["cs.AI","cs.CV","cs.MM"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2022-05-06T16:31:57Z","title":"VFHQ: A High-Quality Dataset and Benchmark for Video Face Super-Resolution"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.03409","kind":"arxiv","version":1},"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:d906628b342e17dae4923234f56237f97a5c75567b233d7869856346f37b67c8","target":"record","created_at":"2026-07-05T04:21:13Z","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":"2487b02ba752a1f7c801eed6223fa023d377b820cc9f66a5a7eab1bfd7381908","cross_cats_sorted":["cs.AI","cs.CV","cs.MM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2022-05-06T16:31:57Z","title_canon_sha256":"6dd34d217cf660c2810fe977487447580dafa1d2e52a313c20660d049b4a15cf"},"schema_version":"1.0","source":{"id":"2205.03409","kind":"arxiv","version":1}},"canonical_sha256":"82f6d18b0d44284a425e273477026215ba09c7102d2b13e5cc4b7884ceef6e8f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"82f6d18b0d44284a425e273477026215ba09c7102d2b13e5cc4b7884ceef6e8f","first_computed_at":"2026-07-05T04:21:13.891839Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:21:13.891839Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Z9bXuXoYVUDzuCHEbKr8MyR+ZF64TSfqHVAB7K+bg+qPA5gACmzW2Ui9VLuhELyax23KG241YEqinCqX3T1LCA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:21:13.892256Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.03409","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d906628b342e17dae4923234f56237f97a5c75567b233d7869856346f37b67c8","sha256:cba48bbf985164bee12ad7acf8e70216ef9e30e4bff459d15cb0c66a0fdbae8a"],"state_sha256":"44c8fa459911c097ed62a25f91cf9dca7bdc79610788d1956833f053a163dfb8"}