{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:FGGUE7YNDY7SQSD7Q4MWED43DL","short_pith_number":"pith:FGGUE7YN","schema_version":"1.0","canonical_sha256":"298d427f0d1e3f28487f8719620f9b1ad84d2feb277623ee36e890a9f706cea8","source":{"kind":"arxiv","id":"2006.12709","version":1},"attestation_state":"computed","paper":{"title":"CIE XYZ Net: Unprocessing Images for Low-Level Computer Vision Tasks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.IV"],"primary_cat":"cs.CV","authors_text":"Abdelrahman Abdelhamed, Abdullah Abuolaim, Abhijith Punnappurath, Mahmoud Afifi, Michael S. Brown","submitted_at":"2020-06-23T02:59:11Z","abstract_excerpt":"Cameras currently allow access to two image states: (i) a minimally processed linear raw-RGB image state (i.e., raw sensor data) or (ii) a highly-processed nonlinear image state (e.g., sRGB). There are many computer vision tasks that work best with a linear image state, such as image deblurring and image dehazing. Unfortunately, the vast majority of images are saved in the nonlinear image state. Because of this, a number of methods have been proposed to \"unprocess\" nonlinear images back to a raw-RGB state. However, existing unprocessing methods have a drawback because raw-RGB images are sensor"},"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":"2006.12709","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-06-23T02:59:11Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"7a921fafefe5728179242449683187d22b3cc0ba047d698bd8233124b63a0613","abstract_canon_sha256":"36aa7f15c365a4eddf4926ee3288b9e1f406219d324232e4063efff8b5cc085b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:12:50.407417Z","signature_b64":"cfzNBVgrk3Jr4DAcqe5Kq1CMb68FW+BGRT7t9ZrHzDiz4e19fDahLw+3dIWfZ14qX9O+r4eV4eXG7ZWD3sD9AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"298d427f0d1e3f28487f8719620f9b1ad84d2feb277623ee36e890a9f706cea8","last_reissued_at":"2026-07-05T01:12:50.406972Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:12:50.406972Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"CIE XYZ Net: Unprocessing Images for Low-Level Computer Vision Tasks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.IV"],"primary_cat":"cs.CV","authors_text":"Abdelrahman Abdelhamed, Abdullah Abuolaim, Abhijith Punnappurath, Mahmoud Afifi, Michael S. Brown","submitted_at":"2020-06-23T02:59:11Z","abstract_excerpt":"Cameras currently allow access to two image states: (i) a minimally processed linear raw-RGB image state (i.e., raw sensor data) or (ii) a highly-processed nonlinear image state (e.g., sRGB). There are many computer vision tasks that work best with a linear image state, such as image deblurring and image dehazing. Unfortunately, the vast majority of images are saved in the nonlinear image state. Because of this, a number of methods have been proposed to \"unprocess\" nonlinear images back to a raw-RGB state. However, existing unprocessing methods have a drawback because raw-RGB images are sensor"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2006.12709","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/2006.12709/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":"2006.12709","created_at":"2026-07-05T01:12:50.407032+00:00"},{"alias_kind":"arxiv_version","alias_value":"2006.12709v1","created_at":"2026-07-05T01:12:50.407032+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2006.12709","created_at":"2026-07-05T01:12:50.407032+00:00"},{"alias_kind":"pith_short_12","alias_value":"FGGUE7YNDY7S","created_at":"2026-07-05T01:12:50.407032+00:00"},{"alias_kind":"pith_short_16","alias_value":"FGGUE7YNDY7SQSD7","created_at":"2026-07-05T01:12:50.407032+00:00"},{"alias_kind":"pith_short_8","alias_value":"FGGUE7YN","created_at":"2026-07-05T01:12:50.407032+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/FGGUE7YNDY7SQSD7Q4MWED43DL","json":"https://pith.science/pith/FGGUE7YNDY7SQSD7Q4MWED43DL.json","graph_json":"https://pith.science/api/pith-number/FGGUE7YNDY7SQSD7Q4MWED43DL/graph.json","events_json":"https://pith.science/api/pith-number/FGGUE7YNDY7SQSD7Q4MWED43DL/events.json","paper":"https://pith.science/paper/FGGUE7YN"},"agent_actions":{"view_html":"https://pith.science/pith/FGGUE7YNDY7SQSD7Q4MWED43DL","download_json":"https://pith.science/pith/FGGUE7YNDY7SQSD7Q4MWED43DL.json","view_paper":"https://pith.science/paper/FGGUE7YN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2006.12709&json=true","fetch_graph":"https://pith.science/api/pith-number/FGGUE7YNDY7SQSD7Q4MWED43DL/graph.json","fetch_events":"https://pith.science/api/pith-number/FGGUE7YNDY7SQSD7Q4MWED43DL/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/FGGUE7YNDY7SQSD7Q4MWED43DL/action/timestamp_anchor","attest_storage":"https://pith.science/pith/FGGUE7YNDY7SQSD7Q4MWED43DL/action/storage_attestation","attest_author":"https://pith.science/pith/FGGUE7YNDY7SQSD7Q4MWED43DL/action/author_attestation","sign_citation":"https://pith.science/pith/FGGUE7YNDY7SQSD7Q4MWED43DL/action/citation_signature","submit_replication":"https://pith.science/pith/FGGUE7YNDY7SQSD7Q4MWED43DL/action/replication_record"}},"created_at":"2026-07-05T01:12:50.407032+00:00","updated_at":"2026-07-05T01:12:50.407032+00:00"}