{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:E5PLBYQNAVWLMGJSGYAHLILAG4","short_pith_number":"pith:E5PLBYQN","schema_version":"1.0","canonical_sha256":"275eb0e20d056cb61932360075a16037194f662fddd093979c5fa34ec46bffa1","source":{"kind":"arxiv","id":"2310.11535","version":2},"attestation_state":"computed","paper":{"title":"Learning Lens Blur Fields","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"eess.IV","authors_text":"Daniel Miau, David B. Lindell, Esther Y. H. Lin, Florian Kainz, Jiawen Chen, Kiriakos N. Kutulakos, Rebecca Lin, Xuaner Cecilia Zhang, Zhecheng Wang","submitted_at":"2023-10-17T19:10:45Z","abstract_excerpt":"Optical blur is an inherent property of any lens system and is challenging to model in modern cameras because of their complex optical elements. To tackle this challenge, we introduce a high-dimensional neural representation of blur$-$$\\textit{the lens blur field}$$-$and a practical method for acquiring it. The lens blur field is a multilayer perceptron (MLP) designed to (1) accurately capture variations of the lens 2D point spread function over image plane location, focus setting and, optionally, depth and (2) represent these variations parametrically as a single, sensor-specific function. Th"},"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":"2310.11535","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2023-10-17T19:10:45Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"da5edd617849042fabae4990d4ee3fe19e0695751ca800fea3d8fa1f04845f2c","abstract_canon_sha256":"97ff29d8f0af4525d7696b1011705c71a6b7fd5c18f63682d3053d4b08243cbb"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:38:22.223011Z","signature_b64":"/5dUAu5zVsrbRVJKsI5bwnvOMRYKAxwV5Ot3edy+WX0icATxfgvVouuw7G3YlZK34XqqFZfeLkzqwgWNl/a2AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"275eb0e20d056cb61932360075a16037194f662fddd093979c5fa34ec46bffa1","last_reissued_at":"2026-07-05T11:38:22.222450Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:38:22.222450Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Learning Lens Blur Fields","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"eess.IV","authors_text":"Daniel Miau, David B. Lindell, Esther Y. H. Lin, Florian Kainz, Jiawen Chen, Kiriakos N. Kutulakos, Rebecca Lin, Xuaner Cecilia Zhang, Zhecheng Wang","submitted_at":"2023-10-17T19:10:45Z","abstract_excerpt":"Optical blur is an inherent property of any lens system and is challenging to model in modern cameras because of their complex optical elements. To tackle this challenge, we introduce a high-dimensional neural representation of blur$-$$\\textit{the lens blur field}$$-$and a practical method for acquiring it. The lens blur field is a multilayer perceptron (MLP) designed to (1) accurately capture variations of the lens 2D point spread function over image plane location, focus setting and, optionally, depth and (2) represent these variations parametrically as a single, sensor-specific function. Th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.11535","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2310.11535/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":"2310.11535","created_at":"2026-07-05T11:38:22.222514+00:00"},{"alias_kind":"arxiv_version","alias_value":"2310.11535v2","created_at":"2026-07-05T11:38:22.222514+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.11535","created_at":"2026-07-05T11:38:22.222514+00:00"},{"alias_kind":"pith_short_12","alias_value":"E5PLBYQNAVWL","created_at":"2026-07-05T11:38:22.222514+00:00"},{"alias_kind":"pith_short_16","alias_value":"E5PLBYQNAVWLMGJS","created_at":"2026-07-05T11:38:22.222514+00:00"},{"alias_kind":"pith_short_8","alias_value":"E5PLBYQN","created_at":"2026-07-05T11:38:22.222514+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/E5PLBYQNAVWLMGJSGYAHLILAG4","json":"https://pith.science/pith/E5PLBYQNAVWLMGJSGYAHLILAG4.json","graph_json":"https://pith.science/api/pith-number/E5PLBYQNAVWLMGJSGYAHLILAG4/graph.json","events_json":"https://pith.science/api/pith-number/E5PLBYQNAVWLMGJSGYAHLILAG4/events.json","paper":"https://pith.science/paper/E5PLBYQN"},"agent_actions":{"view_html":"https://pith.science/pith/E5PLBYQNAVWLMGJSGYAHLILAG4","download_json":"https://pith.science/pith/E5PLBYQNAVWLMGJSGYAHLILAG4.json","view_paper":"https://pith.science/paper/E5PLBYQN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2310.11535&json=true","fetch_graph":"https://pith.science/api/pith-number/E5PLBYQNAVWLMGJSGYAHLILAG4/graph.json","fetch_events":"https://pith.science/api/pith-number/E5PLBYQNAVWLMGJSGYAHLILAG4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/E5PLBYQNAVWLMGJSGYAHLILAG4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/E5PLBYQNAVWLMGJSGYAHLILAG4/action/storage_attestation","attest_author":"https://pith.science/pith/E5PLBYQNAVWLMGJSGYAHLILAG4/action/author_attestation","sign_citation":"https://pith.science/pith/E5PLBYQNAVWLMGJSGYAHLILAG4/action/citation_signature","submit_replication":"https://pith.science/pith/E5PLBYQNAVWLMGJSGYAHLILAG4/action/replication_record"}},"created_at":"2026-07-05T11:38:22.222514+00:00","updated_at":"2026-07-05T11:38:22.222514+00:00"}