{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:FEBEIL2WDNTAOG4QVPFNHAKXOS","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":"d511179003fb875362bf37e57a646d3a499c77f7fefa4107e3f9e3ff6dfa6cc3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-09T14:15:01Z","title_canon_sha256":"244ad8965044cd92ce127d70b75f8bbf1872cc92ebe4c47868141ee3f196d4b0"},"schema_version":"1.0","source":{"id":"1810.04012","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.04012","created_at":"2026-05-17T23:57:39Z"},{"alias_kind":"arxiv_version","alias_value":"1810.04012v1","created_at":"2026-05-17T23:57:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.04012","created_at":"2026-05-17T23:57:39Z"},{"alias_kind":"pith_short_12","alias_value":"FEBEIL2WDNTA","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_16","alias_value":"FEBEIL2WDNTAOG4Q","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_8","alias_value":"FEBEIL2W","created_at":"2026-05-18T12:32:22Z"}],"graph_snapshots":[{"event_id":"sha256:80b9fa7a22e96bbd0938bb78317d9c7ab37a74eb0732d7c3888815e77a653875","target":"graph","created_at":"2026-05-17T23:57:39Z","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"},"paper":{"abstract_excerpt":"Enhancing visual qualities of images plays very important roles in various vision and learning applications. In the past few years, both knowledge-driven maximum a posterior (MAP) with prior modelings and fully data-dependent convolutional neural network (CNN) techniques have been investigated to address specific enhancement tasks. In this paper, by exploiting the advantages of these two types of mechanisms within a complementary propagation perspective, we propose a unified framework, named deep prior ensemble (DPE), for solving various image enhancement tasks. Specifically, we first establis","authors_text":"Lei Zhang, Long Ma, Risheng Liu, Yiyang Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-09T14:15:01Z","title":"Learning Converged Propagations with Deep Prior Ensemble for Image Enhancement"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.04012","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":"sha256:882a51e3f02dae8ea62c0dca129eddbfb86f21bce70008980b6b171fb8fbc160","target":"record","created_at":"2026-05-17T23:57:39Z","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":"d511179003fb875362bf37e57a646d3a499c77f7fefa4107e3f9e3ff6dfa6cc3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-09T14:15:01Z","title_canon_sha256":"244ad8965044cd92ce127d70b75f8bbf1872cc92ebe4c47868141ee3f196d4b0"},"schema_version":"1.0","source":{"id":"1810.04012","kind":"arxiv","version":1}},"canonical_sha256":"2902442f561b66071b90abcad38157748dc84fb8b249cfb1ff029b824d420116","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2902442f561b66071b90abcad38157748dc84fb8b249cfb1ff029b824d420116","first_computed_at":"2026-05-17T23:57:39.731176Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:57:39.731176Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"k99J8z0nRx/iTg6uNviZsM8OLvbkl6imQwXJ7NgxXJlQfXVhizJepUQ+UAoOp4X1BDZqCAQN0H3qOJfFc0NFAA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:57:39.731558Z","signed_message":"canonical_sha256_bytes"},"source_id":"1810.04012","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:882a51e3f02dae8ea62c0dca129eddbfb86f21bce70008980b6b171fb8fbc160","sha256:80b9fa7a22e96bbd0938bb78317d9c7ab37a74eb0732d7c3888815e77a653875"],"state_sha256":"e6d70ae8c98803d9f36d8d5c25019d24266b3ba99e29fe35e2335471851d20a0"}