{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:RL5GZO3BR6ENLDS4GMP7TMFU5E","short_pith_number":"pith:RL5GZO3B","schema_version":"1.0","canonical_sha256":"8afa6cbb618f88d58e5c331ff9b0b4e917593e83624fe96136a852eefeb26a15","source":{"kind":"arxiv","id":"2311.15445","version":1},"attestation_state":"computed","paper":{"title":"FLAIR: A Conditional Diffusion Framework with Applications to Face Video Restoration","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.IV"],"primary_cat":"cs.CV","authors_text":"Jiaming Liu, Shirin Shoushtari, Ulugbek S. Kamilov, Weijie Gan, Yubo Wang, Zihao Zou","submitted_at":"2023-11-26T22:09:18Z","abstract_excerpt":"Face video restoration (FVR) is a challenging but important problem where one seeks to recover a perceptually realistic face videos from a low-quality input. While diffusion probabilistic models (DPMs) have been shown to achieve remarkable performance for face image restoration, they often fail to preserve temporally coherent, high-quality videos, compromising the fidelity of reconstructed faces. We present a new conditional diffusion framework called FLAIR for FVR. FLAIR ensures temporal consistency across frames in a computationally efficient fashion by converting a traditional image DPM int"},"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":"2311.15445","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-11-26T22:09:18Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"d2cccf743e77531d10a4a7c7dd1da27ce0f065ae0fdc58c09d7be46defdc963c","abstract_canon_sha256":"15e0cb51548ecf19833704ce38b49b24a669531fb9aa10cdef6eab3c7e41b1c7"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:17:03.922916Z","signature_b64":"M6CwnDXjLF2xpOcA0CASjDrB8x1qWe/0wj/wMgGMqcjyy0B69z94dQ6UA7V7Y3rFY+WUSgKt5VHpm693lk68DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8afa6cbb618f88d58e5c331ff9b0b4e917593e83624fe96136a852eefeb26a15","last_reissued_at":"2026-07-05T07:17:03.922376Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:17:03.922376Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"FLAIR: A Conditional Diffusion Framework with Applications to Face Video Restoration","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.IV"],"primary_cat":"cs.CV","authors_text":"Jiaming Liu, Shirin Shoushtari, Ulugbek S. Kamilov, Weijie Gan, Yubo Wang, Zihao Zou","submitted_at":"2023-11-26T22:09:18Z","abstract_excerpt":"Face video restoration (FVR) is a challenging but important problem where one seeks to recover a perceptually realistic face videos from a low-quality input. While diffusion probabilistic models (DPMs) have been shown to achieve remarkable performance for face image restoration, they often fail to preserve temporally coherent, high-quality videos, compromising the fidelity of reconstructed faces. We present a new conditional diffusion framework called FLAIR for FVR. FLAIR ensures temporal consistency across frames in a computationally efficient fashion by converting a traditional image DPM int"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.15445","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2311.15445/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":"2311.15445","created_at":"2026-07-05T07:17:03.922446+00:00"},{"alias_kind":"arxiv_version","alias_value":"2311.15445v1","created_at":"2026-07-05T07:17:03.922446+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.15445","created_at":"2026-07-05T07:17:03.922446+00:00"},{"alias_kind":"pith_short_12","alias_value":"RL5GZO3BR6EN","created_at":"2026-07-05T07:17:03.922446+00:00"},{"alias_kind":"pith_short_16","alias_value":"RL5GZO3BR6ENLDS4","created_at":"2026-07-05T07:17:03.922446+00:00"},{"alias_kind":"pith_short_8","alias_value":"RL5GZO3B","created_at":"2026-07-05T07:17:03.922446+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2507.10293","citing_title":"Show and Polish: Reference-Guided Identity Preservation in Face Video Restoration","ref_index":76,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/RL5GZO3BR6ENLDS4GMP7TMFU5E","json":"https://pith.science/pith/RL5GZO3BR6ENLDS4GMP7TMFU5E.json","graph_json":"https://pith.science/api/pith-number/RL5GZO3BR6ENLDS4GMP7TMFU5E/graph.json","events_json":"https://pith.science/api/pith-number/RL5GZO3BR6ENLDS4GMP7TMFU5E/events.json","paper":"https://pith.science/paper/RL5GZO3B"},"agent_actions":{"view_html":"https://pith.science/pith/RL5GZO3BR6ENLDS4GMP7TMFU5E","download_json":"https://pith.science/pith/RL5GZO3BR6ENLDS4GMP7TMFU5E.json","view_paper":"https://pith.science/paper/RL5GZO3B","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2311.15445&json=true","fetch_graph":"https://pith.science/api/pith-number/RL5GZO3BR6ENLDS4GMP7TMFU5E/graph.json","fetch_events":"https://pith.science/api/pith-number/RL5GZO3BR6ENLDS4GMP7TMFU5E/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RL5GZO3BR6ENLDS4GMP7TMFU5E/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RL5GZO3BR6ENLDS4GMP7TMFU5E/action/storage_attestation","attest_author":"https://pith.science/pith/RL5GZO3BR6ENLDS4GMP7TMFU5E/action/author_attestation","sign_citation":"https://pith.science/pith/RL5GZO3BR6ENLDS4GMP7TMFU5E/action/citation_signature","submit_replication":"https://pith.science/pith/RL5GZO3BR6ENLDS4GMP7TMFU5E/action/replication_record"}},"created_at":"2026-07-05T07:17:03.922446+00:00","updated_at":"2026-07-05T07:17:03.922446+00:00"}