{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:PBAQMRNOLLEQBGXASKZZRRHVCR","short_pith_number":"pith:PBAQMRNO","schema_version":"1.0","canonical_sha256":"78410645ae5ac9009ae092b398c4f51451a674e88392cbc55aad264f3f87826d","source":{"kind":"arxiv","id":"2412.08975","version":1},"attestation_state":"computed","paper":{"title":"Elevating Flow-Guided Video Inpainting with Reference Generation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Joon-Young Lee, Sangyoun Lee, Seoung Wug Oh, Suhwan Cho","submitted_at":"2024-12-12T06:13:00Z","abstract_excerpt":"Video inpainting (VI) is a challenging task that requires effective propagation of observable content across frames while simultaneously generating new content not present in the original video. In this study, we propose a robust and practical VI framework that leverages a large generative model for reference generation in combination with an advanced pixel propagation algorithm. Powered by a strong generative model, our method not only significantly enhances frame-level quality for object removal but also synthesizes new content in the missing areas based on user-provided text prompts. For pi"},"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":"2412.08975","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-12T06:13:00Z","cross_cats_sorted":[],"title_canon_sha256":"9f6cb99a972ee2e3da79e82b38212ed41707dc4b4395c7bf12e70c534430cef9","abstract_canon_sha256":"ab2381b591b7d6abfe991e2cdbb6f564f5585d402bcf368cf449e33bb7e7fc17"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:48:04.741915Z","signature_b64":"XiM0zfiG1RBLTbUxzEDr/STwwTUID33Z/+ALMDQHplnrU6vqmAd3HNaXeYOfv91g4BH4vnIDFxGKdAgc78/NBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"78410645ae5ac9009ae092b398c4f51451a674e88392cbc55aad264f3f87826d","last_reissued_at":"2026-07-05T09:48:04.741416Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:48:04.741416Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Elevating Flow-Guided Video Inpainting with Reference Generation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Joon-Young Lee, Sangyoun Lee, Seoung Wug Oh, Suhwan Cho","submitted_at":"2024-12-12T06:13:00Z","abstract_excerpt":"Video inpainting (VI) is a challenging task that requires effective propagation of observable content across frames while simultaneously generating new content not present in the original video. In this study, we propose a robust and practical VI framework that leverages a large generative model for reference generation in combination with an advanced pixel propagation algorithm. Powered by a strong generative model, our method not only significantly enhances frame-level quality for object removal but also synthesizes new content in the missing areas based on user-provided text prompts. For pi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.08975","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/2412.08975/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":"2412.08975","created_at":"2026-07-05T09:48:04.741477+00:00"},{"alias_kind":"arxiv_version","alias_value":"2412.08975v1","created_at":"2026-07-05T09:48:04.741477+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.08975","created_at":"2026-07-05T09:48:04.741477+00:00"},{"alias_kind":"pith_short_12","alias_value":"PBAQMRNOLLEQ","created_at":"2026-07-05T09:48:04.741477+00:00"},{"alias_kind":"pith_short_16","alias_value":"PBAQMRNOLLEQBGXA","created_at":"2026-07-05T09:48:04.741477+00:00"},{"alias_kind":"pith_short_8","alias_value":"PBAQMRNO","created_at":"2026-07-05T09:48:04.741477+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/PBAQMRNOLLEQBGXASKZZRRHVCR","json":"https://pith.science/pith/PBAQMRNOLLEQBGXASKZZRRHVCR.json","graph_json":"https://pith.science/api/pith-number/PBAQMRNOLLEQBGXASKZZRRHVCR/graph.json","events_json":"https://pith.science/api/pith-number/PBAQMRNOLLEQBGXASKZZRRHVCR/events.json","paper":"https://pith.science/paper/PBAQMRNO"},"agent_actions":{"view_html":"https://pith.science/pith/PBAQMRNOLLEQBGXASKZZRRHVCR","download_json":"https://pith.science/pith/PBAQMRNOLLEQBGXASKZZRRHVCR.json","view_paper":"https://pith.science/paper/PBAQMRNO","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2412.08975&json=true","fetch_graph":"https://pith.science/api/pith-number/PBAQMRNOLLEQBGXASKZZRRHVCR/graph.json","fetch_events":"https://pith.science/api/pith-number/PBAQMRNOLLEQBGXASKZZRRHVCR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/PBAQMRNOLLEQBGXASKZZRRHVCR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/PBAQMRNOLLEQBGXASKZZRRHVCR/action/storage_attestation","attest_author":"https://pith.science/pith/PBAQMRNOLLEQBGXASKZZRRHVCR/action/author_attestation","sign_citation":"https://pith.science/pith/PBAQMRNOLLEQBGXASKZZRRHVCR/action/citation_signature","submit_replication":"https://pith.science/pith/PBAQMRNOLLEQBGXASKZZRRHVCR/action/replication_record"}},"created_at":"2026-07-05T09:48:04.741477+00:00","updated_at":"2026-07-05T09:48:04.741477+00:00"}