{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:SYH64HURPNE475UK42CTZQDEOH","short_pith_number":"pith:SYH64HUR","canonical_record":{"source":{"id":"2301.06184","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-01-15T20:47:38Z","cross_cats_sorted":[],"title_canon_sha256":"9a1361746b638713634b66b8d1ad679d72abb985951d63ec2233c2baaa07ed05","abstract_canon_sha256":"f284bc83065e00b80f639ecafb4d1b3d9f17684120d6cb33835157e3a42a6617"},"schema_version":"1.0"},"canonical_sha256":"960fee1e917b49cff68ae6853cc06471f3b5f948fadf734776764c32cb3e12f3","source":{"kind":"arxiv","id":"2301.06184","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.06184","created_at":"2026-07-05T05:33:28Z"},{"alias_kind":"arxiv_version","alias_value":"2301.06184v1","created_at":"2026-07-05T05:33:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.06184","created_at":"2026-07-05T05:33:28Z"},{"alias_kind":"pith_short_12","alias_value":"SYH64HURPNE4","created_at":"2026-07-05T05:33:28Z"},{"alias_kind":"pith_short_16","alias_value":"SYH64HURPNE475UK","created_at":"2026-07-05T05:33:28Z"},{"alias_kind":"pith_short_8","alias_value":"SYH64HUR","created_at":"2026-07-05T05:33:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:SYH64HURPNE475UK42CTZQDEOH","target":"record","payload":{"canonical_record":{"source":{"id":"2301.06184","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-01-15T20:47:38Z","cross_cats_sorted":[],"title_canon_sha256":"9a1361746b638713634b66b8d1ad679d72abb985951d63ec2233c2baaa07ed05","abstract_canon_sha256":"f284bc83065e00b80f639ecafb4d1b3d9f17684120d6cb33835157e3a42a6617"},"schema_version":"1.0"},"canonical_sha256":"960fee1e917b49cff68ae6853cc06471f3b5f948fadf734776764c32cb3e12f3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:33:28.944670Z","signature_b64":"QIV9Iao7cu8rGWT7b71XSe3EuCH6wieF2tzX+Z2YMII/TJp0puGFuvLI+WLreFj6Q0iBn6TBA0qIoF9iCkKjCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"960fee1e917b49cff68ae6853cc06471f3b5f948fadf734776764c32cb3e12f3","last_reissued_at":"2026-07-05T05:33:28.944190Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:33:28.944190Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2301.06184","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":"2026-07-05T05:33:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"c4MPlAXEoDD9RLtmAtnVNaEcQ4N44xnTd8gqusK3VbXXrzLgW+x8/7Xwk5OBAMceV1rw7ETE16A3GAjyJ73SDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T08:04:46.497603Z"},"content_sha256":"59a1be4d8a1ebf6ac620177532a273a05b27fa02afa7a5be4a92947895384159","schema_version":"1.0","event_id":"sha256:59a1be4d8a1ebf6ac620177532a273a05b27fa02afa7a5be4a92947895384159"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:SYH64HURPNE475UK42CTZQDEOH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"LitAR: Visually Coherent Lighting for Mobile Augmented Reality","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chongyang Ma, Haibin Huang, Tian Guo, Yiqin Zhao","submitted_at":"2023-01-15T20:47:38Z","abstract_excerpt":"An accurate understanding of omnidirectional environment lighting is crucial for high-quality virtual object rendering in mobile augmented reality (AR). In particular, to support reflective rendering, existing methods have leveraged deep learning models to estimate or have used physical light probes to capture physical lighting, typically represented in the form of an environment map. However, these methods often fail to provide visually coherent details or require additional setups. For example, the commercial framework ARKit uses a convolutional neural network that can generate realistic env"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.06184","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/2301.06184/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":"2026-07-05T05:33:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E/E0lJJTiC/QSVsX+2vwoWAft8c40d17lY3dFGPSlYpvQHnXSrvUwoGWfVbbM4LAzr2BoJfJPZFfFG5fECDZBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T08:04:46.498219Z"},"content_sha256":"5fa9b833f83a52396b2956bbe7b0027ce31f5aadb3028e1f0daa0815227bd7a7","schema_version":"1.0","event_id":"sha256:5fa9b833f83a52396b2956bbe7b0027ce31f5aadb3028e1f0daa0815227bd7a7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SYH64HURPNE475UK42CTZQDEOH/bundle.json","state_url":"https://pith.science/pith/SYH64HURPNE475UK42CTZQDEOH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SYH64HURPNE475UK42CTZQDEOH/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":"2026-08-13T08:04:46Z","links":{"resolver":"https://pith.science/pith/SYH64HURPNE475UK42CTZQDEOH","bundle":"https://pith.science/pith/SYH64HURPNE475UK42CTZQDEOH/bundle.json","state":"https://pith.science/pith/SYH64HURPNE475UK42CTZQDEOH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SYH64HURPNE475UK42CTZQDEOH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:SYH64HURPNE475UK42CTZQDEOH","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":"f284bc83065e00b80f639ecafb4d1b3d9f17684120d6cb33835157e3a42a6617","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-01-15T20:47:38Z","title_canon_sha256":"9a1361746b638713634b66b8d1ad679d72abb985951d63ec2233c2baaa07ed05"},"schema_version":"1.0","source":{"id":"2301.06184","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.06184","created_at":"2026-07-05T05:33:28Z"},{"alias_kind":"arxiv_version","alias_value":"2301.06184v1","created_at":"2026-07-05T05:33:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.06184","created_at":"2026-07-05T05:33:28Z"},{"alias_kind":"pith_short_12","alias_value":"SYH64HURPNE4","created_at":"2026-07-05T05:33:28Z"},{"alias_kind":"pith_short_16","alias_value":"SYH64HURPNE475UK","created_at":"2026-07-05T05:33:28Z"},{"alias_kind":"pith_short_8","alias_value":"SYH64HUR","created_at":"2026-07-05T05:33:28Z"}],"graph_snapshots":[{"event_id":"sha256:5fa9b833f83a52396b2956bbe7b0027ce31f5aadb3028e1f0daa0815227bd7a7","target":"graph","created_at":"2026-07-05T05:33:28Z","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/2301.06184/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"An accurate understanding of omnidirectional environment lighting is crucial for high-quality virtual object rendering in mobile augmented reality (AR). In particular, to support reflective rendering, existing methods have leveraged deep learning models to estimate or have used physical light probes to capture physical lighting, typically represented in the form of an environment map. However, these methods often fail to provide visually coherent details or require additional setups. For example, the commercial framework ARKit uses a convolutional neural network that can generate realistic env","authors_text":"Chongyang Ma, Haibin Huang, Tian Guo, Yiqin Zhao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-01-15T20:47:38Z","title":"LitAR: Visually Coherent Lighting for Mobile Augmented Reality"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.06184","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":"sha256:59a1be4d8a1ebf6ac620177532a273a05b27fa02afa7a5be4a92947895384159","target":"record","created_at":"2026-07-05T05:33:28Z","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":"f284bc83065e00b80f639ecafb4d1b3d9f17684120d6cb33835157e3a42a6617","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-01-15T20:47:38Z","title_canon_sha256":"9a1361746b638713634b66b8d1ad679d72abb985951d63ec2233c2baaa07ed05"},"schema_version":"1.0","source":{"id":"2301.06184","kind":"arxiv","version":1}},"canonical_sha256":"960fee1e917b49cff68ae6853cc06471f3b5f948fadf734776764c32cb3e12f3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"960fee1e917b49cff68ae6853cc06471f3b5f948fadf734776764c32cb3e12f3","first_computed_at":"2026-07-05T05:33:28.944190Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:33:28.944190Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QIV9Iao7cu8rGWT7b71XSe3EuCH6wieF2tzX+Z2YMII/TJp0puGFuvLI+WLreFj6Q0iBn6TBA0qIoF9iCkKjCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:33:28.944670Z","signed_message":"canonical_sha256_bytes"},"source_id":"2301.06184","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:59a1be4d8a1ebf6ac620177532a273a05b27fa02afa7a5be4a92947895384159","sha256:5fa9b833f83a52396b2956bbe7b0027ce31f5aadb3028e1f0daa0815227bd7a7"],"state_sha256":"a5939bab9e4bbe1b765cbe3e25ea1344fcf8122059af194dcea96c18e79eea25"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/pdQ4Aio8avbmAwIVZSgKkrMMOgk3yWPf1Tp6Wp2KjMLkHIiEyDdEeAdqXZaWY5Qz1CR29O0sFHnGJkfwC+/Cg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T08:04:46.501953Z","bundle_sha256":"302db473393df487c661a9de67ec4c6b0d12ea9d75a4485eb6346ed8b7dba459"}}