{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:J4RNW3X4WFWBZTPRXS3TYO3HLQ","short_pith_number":"pith:J4RNW3X4","canonical_record":{"source":{"id":"2406.11469","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-06-17T12:31:03Z","cross_cats_sorted":[],"title_canon_sha256":"f12f3c9785e7b776337f6e2a8fbbd00dd46c32bbe5b9bd08c85e79f414184e9b","abstract_canon_sha256":"6b5ebca9d429c558854ab4ac7bda093dd15f58981d53a0c64a13d26eaae46515"},"schema_version":"1.0"},"canonical_sha256":"4f22db6efcb16c1ccdf1bcb73c3b675c1a2a1e1b00b6b5fb400dfa5caffbdec0","source":{"kind":"arxiv","id":"2406.11469","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.11469","created_at":"2026-07-05T08:32:53Z"},{"alias_kind":"arxiv_version","alias_value":"2406.11469v1","created_at":"2026-07-05T08:32:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.11469","created_at":"2026-07-05T08:32:53Z"},{"alias_kind":"pith_short_12","alias_value":"J4RNW3X4WFWB","created_at":"2026-07-05T08:32:53Z"},{"alias_kind":"pith_short_16","alias_value":"J4RNW3X4WFWBZTPR","created_at":"2026-07-05T08:32:53Z"},{"alias_kind":"pith_short_8","alias_value":"J4RNW3X4","created_at":"2026-07-05T08:32:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:J4RNW3X4WFWBZTPRXS3TYO3HLQ","target":"record","payload":{"canonical_record":{"source":{"id":"2406.11469","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-06-17T12:31:03Z","cross_cats_sorted":[],"title_canon_sha256":"f12f3c9785e7b776337f6e2a8fbbd00dd46c32bbe5b9bd08c85e79f414184e9b","abstract_canon_sha256":"6b5ebca9d429c558854ab4ac7bda093dd15f58981d53a0c64a13d26eaae46515"},"schema_version":"1.0"},"canonical_sha256":"4f22db6efcb16c1ccdf1bcb73c3b675c1a2a1e1b00b6b5fb400dfa5caffbdec0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:32:53.713194Z","signature_b64":"/PloAXIJCVr11VyKcsoujKnjSRojwxUmoIMTWdelzq3eXvTiikqvTDBigjge9GTUjxA3R3SdLuVxGHahrdvtBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4f22db6efcb16c1ccdf1bcb73c3b675c1a2a1e1b00b6b5fb400dfa5caffbdec0","last_reissued_at":"2026-07-05T08:32:53.712744Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:32:53.712744Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.11469","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:32:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yWR+nGeF9OD2Z/KyWjHszBsrIcCF87+bjmpKYrDYr6E01lx5re78yZLtAK/UU0G9ibAVIh/VxjE3JnjRXOYmBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T18:08:19.452467Z"},"content_sha256":"f0bebdab9acb545eb511cc069e42f68b1839c50c52bf5017d140aa1697147419","schema_version":"1.0","event_id":"sha256:f0bebdab9acb545eb511cc069e42f68b1839c50c52bf5017d140aa1697147419"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:J4RNW3X4WFWBZTPRXS3TYO3HLQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"RMFA-Net: A Neural ISP for Real RAW to RGB Image Reconstruction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"eess.IV","authors_text":"Fei Li, Peng Jia, Wenbo Hou","submitted_at":"2024-06-17T12:31:03Z","abstract_excerpt":"Deep learning-based ISP algorithms have demonstrated significant potential in raw2rgb reconstruction. However, existing networks have not fully considered the specific characteristics of raw data, such as black level and CFA, which can negatively impact texture and color if mishandled. Moreover, uneven exposure in raw data is also not considered carefully, leading to adverse effects on contrast and brightness. In this paper, we introduce RMFA-Net to tackle these problems. We perform implicit black level correction to mitigate color shifts in dim scenes. To preserve high-frequency information a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.11469","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/2406.11469/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:32:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VRN6voPfhmKGJ5CBIty2e+xIMZElQCaMrzPs4ozfOxiHD1ZI5ikWtjAbQV1Hi1m/AAxywWJmrJO9h9XR42zIBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T18:08:19.452973Z"},"content_sha256":"c53a17f75ea7666df8b0001df797a5c0bd856702ddf535ff0d3fc7e7f7296174","schema_version":"1.0","event_id":"sha256:c53a17f75ea7666df8b0001df797a5c0bd856702ddf535ff0d3fc7e7f7296174"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/J4RNW3X4WFWBZTPRXS3TYO3HLQ/bundle.json","state_url":"https://pith.science/pith/J4RNW3X4WFWBZTPRXS3TYO3HLQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/J4RNW3X4WFWBZTPRXS3TYO3HLQ/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-04T18:08:19Z","links":{"resolver":"https://pith.science/pith/J4RNW3X4WFWBZTPRXS3TYO3HLQ","bundle":"https://pith.science/pith/J4RNW3X4WFWBZTPRXS3TYO3HLQ/bundle.json","state":"https://pith.science/pith/J4RNW3X4WFWBZTPRXS3TYO3HLQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/J4RNW3X4WFWBZTPRXS3TYO3HLQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:J4RNW3X4WFWBZTPRXS3TYO3HLQ","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":"6b5ebca9d429c558854ab4ac7bda093dd15f58981d53a0c64a13d26eaae46515","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-06-17T12:31:03Z","title_canon_sha256":"f12f3c9785e7b776337f6e2a8fbbd00dd46c32bbe5b9bd08c85e79f414184e9b"},"schema_version":"1.0","source":{"id":"2406.11469","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.11469","created_at":"2026-07-05T08:32:53Z"},{"alias_kind":"arxiv_version","alias_value":"2406.11469v1","created_at":"2026-07-05T08:32:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.11469","created_at":"2026-07-05T08:32:53Z"},{"alias_kind":"pith_short_12","alias_value":"J4RNW3X4WFWB","created_at":"2026-07-05T08:32:53Z"},{"alias_kind":"pith_short_16","alias_value":"J4RNW3X4WFWBZTPR","created_at":"2026-07-05T08:32:53Z"},{"alias_kind":"pith_short_8","alias_value":"J4RNW3X4","created_at":"2026-07-05T08:32:53Z"}],"graph_snapshots":[{"event_id":"sha256:c53a17f75ea7666df8b0001df797a5c0bd856702ddf535ff0d3fc7e7f7296174","target":"graph","created_at":"2026-07-05T08:32:53Z","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/2406.11469/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning-based ISP algorithms have demonstrated significant potential in raw2rgb reconstruction. However, existing networks have not fully considered the specific characteristics of raw data, such as black level and CFA, which can negatively impact texture and color if mishandled. Moreover, uneven exposure in raw data is also not considered carefully, leading to adverse effects on contrast and brightness. In this paper, we introduce RMFA-Net to tackle these problems. We perform implicit black level correction to mitigate color shifts in dim scenes. To preserve high-frequency information a","authors_text":"Fei Li, Peng Jia, Wenbo Hou","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-06-17T12:31:03Z","title":"RMFA-Net: A Neural ISP for Real RAW to RGB Image Reconstruction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.11469","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:f0bebdab9acb545eb511cc069e42f68b1839c50c52bf5017d140aa1697147419","target":"record","created_at":"2026-07-05T08:32:53Z","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":"6b5ebca9d429c558854ab4ac7bda093dd15f58981d53a0c64a13d26eaae46515","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-06-17T12:31:03Z","title_canon_sha256":"f12f3c9785e7b776337f6e2a8fbbd00dd46c32bbe5b9bd08c85e79f414184e9b"},"schema_version":"1.0","source":{"id":"2406.11469","kind":"arxiv","version":1}},"canonical_sha256":"4f22db6efcb16c1ccdf1bcb73c3b675c1a2a1e1b00b6b5fb400dfa5caffbdec0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4f22db6efcb16c1ccdf1bcb73c3b675c1a2a1e1b00b6b5fb400dfa5caffbdec0","first_computed_at":"2026-07-05T08:32:53.712744Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:32:53.712744Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/PloAXIJCVr11VyKcsoujKnjSRojwxUmoIMTWdelzq3eXvTiikqvTDBigjge9GTUjxA3R3SdLuVxGHahrdvtBw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:32:53.713194Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.11469","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f0bebdab9acb545eb511cc069e42f68b1839c50c52bf5017d140aa1697147419","sha256:c53a17f75ea7666df8b0001df797a5c0bd856702ddf535ff0d3fc7e7f7296174"],"state_sha256":"7240ff3b6b9df422eb3b2dcc154d8b1ed305751aba9a608a9d48b6c3bbe1cb23"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9N8N27Wj/YC57vJXuoR7D/IsF88twUtptx4OZGgidfKENC8Z9mNNJt0hHftHgxQaNRri9G6VZz/C8OWXJMTUCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T18:08:19.458342Z","bundle_sha256":"7d2ab1e166345ba26d1ebc749e53194f29cd432cb4490145698b7f168c4ea7fa"}}