{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:LGPNFNNHP5MUXXC6DKEXLXRTQG","short_pith_number":"pith:LGPNFNNH","schema_version":"1.0","canonical_sha256":"599ed2b5a77f594bdc5e1a8975de3381a92478f42a7119225f7734f396657d7c","source":{"kind":"arxiv","id":"1901.02840","version":2},"attestation_state":"computed","paper":{"title":"GIF2Video: Color Dequantization and Temporal Interpolation of GIF images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chuan Wang, Haibin Huang, Jue Wang, Minh Hoai, Tong He, Yang Wang","submitted_at":"2019-01-09T17:31:11Z","abstract_excerpt":"Graphics Interchange Format (GIF) is a highly portable graphics format that is ubiquitous on the Internet. Despite their small sizes, GIF images often contain undesirable visual artifacts such as flat color regions, false contours, color shift, and dotted patterns. In this paper, we propose GIF2Video, the first learning-based method for enhancing the visual quality of GIFs in the wild. We focus on the challenging task of GIF restoration by recovering information lost in the three steps of GIF creation: frame sampling, color quantization, and color dithering. We first propose a novel CNN archit"},"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":"1901.02840","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-01-09T17:31:11Z","cross_cats_sorted":[],"title_canon_sha256":"082f33e38d5650955794a499853ac9d8953ee41d35f572642bd946fecc05f434","abstract_canon_sha256":"cb4668dc0b125ff5a4cf0adc05d7e705fcb281d13b7cc531dc17b41cb12893c9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:49:02.308885Z","signature_b64":"bUWwGuoMxFyJg9xu8nOqUi6nxFRYIIlWR05GzLcj00g3qVSnXKZwNWGiH2Gyg4Wo1KM/kFVYrbot/CPaFkBBCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"599ed2b5a77f594bdc5e1a8975de3381a92478f42a7119225f7734f396657d7c","last_reissued_at":"2026-05-17T23:49:02.308496Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:49:02.308496Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"GIF2Video: Color Dequantization and Temporal Interpolation of GIF images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chuan Wang, Haibin Huang, Jue Wang, Minh Hoai, Tong He, Yang Wang","submitted_at":"2019-01-09T17:31:11Z","abstract_excerpt":"Graphics Interchange Format (GIF) is a highly portable graphics format that is ubiquitous on the Internet. Despite their small sizes, GIF images often contain undesirable visual artifacts such as flat color regions, false contours, color shift, and dotted patterns. In this paper, we propose GIF2Video, the first learning-based method for enhancing the visual quality of GIFs in the wild. We focus on the challenging task of GIF restoration by recovering information lost in the three steps of GIF creation: frame sampling, color quantization, and color dithering. We first propose a novel CNN archit"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.02840","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":""},"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":"1901.02840","created_at":"2026-05-17T23:49:02.308557+00:00"},{"alias_kind":"arxiv_version","alias_value":"1901.02840v2","created_at":"2026-05-17T23:49:02.308557+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.02840","created_at":"2026-05-17T23:49:02.308557+00:00"},{"alias_kind":"pith_short_12","alias_value":"LGPNFNNHP5MU","created_at":"2026-05-18T12:33:21.387695+00:00"},{"alias_kind":"pith_short_16","alias_value":"LGPNFNNHP5MUXXC6","created_at":"2026-05-18T12:33:21.387695+00:00"},{"alias_kind":"pith_short_8","alias_value":"LGPNFNNH","created_at":"2026-05-18T12:33:21.387695+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/LGPNFNNHP5MUXXC6DKEXLXRTQG","json":"https://pith.science/pith/LGPNFNNHP5MUXXC6DKEXLXRTQG.json","graph_json":"https://pith.science/api/pith-number/LGPNFNNHP5MUXXC6DKEXLXRTQG/graph.json","events_json":"https://pith.science/api/pith-number/LGPNFNNHP5MUXXC6DKEXLXRTQG/events.json","paper":"https://pith.science/paper/LGPNFNNH"},"agent_actions":{"view_html":"https://pith.science/pith/LGPNFNNHP5MUXXC6DKEXLXRTQG","download_json":"https://pith.science/pith/LGPNFNNHP5MUXXC6DKEXLXRTQG.json","view_paper":"https://pith.science/paper/LGPNFNNH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1901.02840&json=true","fetch_graph":"https://pith.science/api/pith-number/LGPNFNNHP5MUXXC6DKEXLXRTQG/graph.json","fetch_events":"https://pith.science/api/pith-number/LGPNFNNHP5MUXXC6DKEXLXRTQG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/LGPNFNNHP5MUXXC6DKEXLXRTQG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/LGPNFNNHP5MUXXC6DKEXLXRTQG/action/storage_attestation","attest_author":"https://pith.science/pith/LGPNFNNHP5MUXXC6DKEXLXRTQG/action/author_attestation","sign_citation":"https://pith.science/pith/LGPNFNNHP5MUXXC6DKEXLXRTQG/action/citation_signature","submit_replication":"https://pith.science/pith/LGPNFNNHP5MUXXC6DKEXLXRTQG/action/replication_record"}},"created_at":"2026-05-17T23:49:02.308557+00:00","updated_at":"2026-05-17T23:49:02.308557+00:00"}