{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:2KURW7ESBKHVSBR7QYGHN35JWQ","short_pith_number":"pith:2KURW7ES","canonical_record":{"source":{"id":"2409.02497","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-09-04T07:46:42Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"88d651e8e84d3f753628b9dbcbcbbeb5adb55810a1364a5b218bd92ed6eb4976","abstract_canon_sha256":"118057a837b1c1bc163375151a1cdb876aa3d3e58b18ba500c1eb93d26439a28"},"schema_version":"1.0"},"canonical_sha256":"d2a91b7c920a8f59063f860c76efa9b4133571dac92f903c43ad861676c5a7f6","source":{"kind":"arxiv","id":"2409.02497","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.02497","created_at":"2026-07-05T09:03:05Z"},{"alias_kind":"arxiv_version","alias_value":"2409.02497v1","created_at":"2026-07-05T09:03:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.02497","created_at":"2026-07-05T09:03:05Z"},{"alias_kind":"pith_short_12","alias_value":"2KURW7ESBKHV","created_at":"2026-07-05T09:03:05Z"},{"alias_kind":"pith_short_16","alias_value":"2KURW7ESBKHVSBR7","created_at":"2026-07-05T09:03:05Z"},{"alias_kind":"pith_short_8","alias_value":"2KURW7ES","created_at":"2026-07-05T09:03:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:2KURW7ESBKHVSBR7QYGHN35JWQ","target":"record","payload":{"canonical_record":{"source":{"id":"2409.02497","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-09-04T07:46:42Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"88d651e8e84d3f753628b9dbcbcbbeb5adb55810a1364a5b218bd92ed6eb4976","abstract_canon_sha256":"118057a837b1c1bc163375151a1cdb876aa3d3e58b18ba500c1eb93d26439a28"},"schema_version":"1.0"},"canonical_sha256":"d2a91b7c920a8f59063f860c76efa9b4133571dac92f903c43ad861676c5a7f6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:03:05.750160Z","signature_b64":"h+CLa+8dJQe4bNZdPffaZeKRORSb0mAgWiD46P2IEO2KzBxhtdLDMG83iNAATiHo6LuGHK4xaXv+p3C1+d/yBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d2a91b7c920a8f59063f860c76efa9b4133571dac92f903c43ad861676c5a7f6","last_reissued_at":"2026-07-05T09:03:05.749644Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:03:05.749644Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2409.02497","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":"2026-07-05T09:03:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PXwiT5Mcm2GggDqGfrrx1hEaautJZzO+XCJQiP+2/utZDo/mcYPgJArSdZKum7l1zQJxa9tzqyQHP85OgeRSCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T04:18:20.211127Z"},"content_sha256":"a39730271a93fbdfe57e96219b78ff030468d9054e402e10dd0a9fe7c4749994","schema_version":"1.0","event_id":"sha256:a39730271a93fbdfe57e96219b78ff030468d9054e402e10dd0a9fe7c4749994"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:2KURW7ESBKHVSBR7QYGHN35JWQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Learnable Color Correction Matrix for RAW Reconstruction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"eess.IV","authors_text":"Anqi Liu, Shiyi Mu, Shugong Xu","submitted_at":"2024-09-04T07:46:42Z","abstract_excerpt":"Autonomous driving algorithms usually employ sRGB images as model input due to their compatibility with the human visual system. However, visually pleasing sRGB images are possibly sub-optimal for downstream tasks when compared to RAW images. The availability of RAW images is constrained by the difficulties in collecting real-world driving data and the associated challenges of annotation. To address this limitation and support research in RAW-domain driving perception, we design a novel and ultra-lightweight RAW reconstruction method. The proposed model introduces a learnable color correction "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.02497","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/2409.02497/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":"2026-07-05T09:03:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"l3Yb0zIlpvW01BRwDnMxlQtZyBkzl9dMX3kmBeCGDxn/CbPX59fo3Sfc14/L9wBog2FVj164hOPG5sE2CaHMBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T04:18:20.211632Z"},"content_sha256":"e0984dfafa1eb91a1369d0e1af941eef9309369fd4d27f28b2d746789a3ccab9","schema_version":"1.0","event_id":"sha256:e0984dfafa1eb91a1369d0e1af941eef9309369fd4d27f28b2d746789a3ccab9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2KURW7ESBKHVSBR7QYGHN35JWQ/bundle.json","state_url":"https://pith.science/pith/2KURW7ESBKHVSBR7QYGHN35JWQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2KURW7ESBKHVSBR7QYGHN35JWQ/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":"2026-08-05T04:18:20Z","links":{"resolver":"https://pith.science/pith/2KURW7ESBKHVSBR7QYGHN35JWQ","bundle":"https://pith.science/pith/2KURW7ESBKHVSBR7QYGHN35JWQ/bundle.json","state":"https://pith.science/pith/2KURW7ESBKHVSBR7QYGHN35JWQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2KURW7ESBKHVSBR7QYGHN35JWQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:2KURW7ESBKHVSBR7QYGHN35JWQ","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":"118057a837b1c1bc163375151a1cdb876aa3d3e58b18ba500c1eb93d26439a28","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-09-04T07:46:42Z","title_canon_sha256":"88d651e8e84d3f753628b9dbcbcbbeb5adb55810a1364a5b218bd92ed6eb4976"},"schema_version":"1.0","source":{"id":"2409.02497","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.02497","created_at":"2026-07-05T09:03:05Z"},{"alias_kind":"arxiv_version","alias_value":"2409.02497v1","created_at":"2026-07-05T09:03:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.02497","created_at":"2026-07-05T09:03:05Z"},{"alias_kind":"pith_short_12","alias_value":"2KURW7ESBKHV","created_at":"2026-07-05T09:03:05Z"},{"alias_kind":"pith_short_16","alias_value":"2KURW7ESBKHVSBR7","created_at":"2026-07-05T09:03:05Z"},{"alias_kind":"pith_short_8","alias_value":"2KURW7ES","created_at":"2026-07-05T09:03:05Z"}],"graph_snapshots":[{"event_id":"sha256:e0984dfafa1eb91a1369d0e1af941eef9309369fd4d27f28b2d746789a3ccab9","target":"graph","created_at":"2026-07-05T09:03:05Z","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/2409.02497/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Autonomous driving algorithms usually employ sRGB images as model input due to their compatibility with the human visual system. However, visually pleasing sRGB images are possibly sub-optimal for downstream tasks when compared to RAW images. The availability of RAW images is constrained by the difficulties in collecting real-world driving data and the associated challenges of annotation. To address this limitation and support research in RAW-domain driving perception, we design a novel and ultra-lightweight RAW reconstruction method. The proposed model introduces a learnable color correction ","authors_text":"Anqi Liu, Shiyi Mu, Shugong Xu","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-09-04T07:46:42Z","title":"A Learnable Color Correction Matrix for RAW Reconstruction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.02497","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:a39730271a93fbdfe57e96219b78ff030468d9054e402e10dd0a9fe7c4749994","target":"record","created_at":"2026-07-05T09:03:05Z","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":"118057a837b1c1bc163375151a1cdb876aa3d3e58b18ba500c1eb93d26439a28","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2024-09-04T07:46:42Z","title_canon_sha256":"88d651e8e84d3f753628b9dbcbcbbeb5adb55810a1364a5b218bd92ed6eb4976"},"schema_version":"1.0","source":{"id":"2409.02497","kind":"arxiv","version":1}},"canonical_sha256":"d2a91b7c920a8f59063f860c76efa9b4133571dac92f903c43ad861676c5a7f6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d2a91b7c920a8f59063f860c76efa9b4133571dac92f903c43ad861676c5a7f6","first_computed_at":"2026-07-05T09:03:05.749644Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:03:05.749644Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"h+CLa+8dJQe4bNZdPffaZeKRORSb0mAgWiD46P2IEO2KzBxhtdLDMG83iNAATiHo6LuGHK4xaXv+p3C1+d/yBg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:03:05.750160Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.02497","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a39730271a93fbdfe57e96219b78ff030468d9054e402e10dd0a9fe7c4749994","sha256:e0984dfafa1eb91a1369d0e1af941eef9309369fd4d27f28b2d746789a3ccab9"],"state_sha256":"4f5a1dbeede050e8754f6f612c083e525dd5c0cb5de640a54bb4b1ee5bcc8725"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BCmwcEJiPOKTWefeAm9soMgjptpfStvfu8H6Uv3AqLAMiIiSNhL37mJGZGW1llBALVu6kfuwZqj+HP9u+3iDAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T04:18:20.216731Z","bundle_sha256":"a7571fd347a6f63813d505468a1eddf0b7e4b84bee1859e8a95af826eee49f68"}}