{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:PC4WDB6WYIQF6OKYWKCRBCDH2D","short_pith_number":"pith:PC4WDB6W","canonical_record":{"source":{"id":"2305.12296","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-20T22:27:41Z","cross_cats_sorted":["cs.AI","cs.GR"],"title_canon_sha256":"b984d2c414c10f0a04b2d308943423422decddd9fc5728bfb680d0cf1f1badda","abstract_canon_sha256":"b0ac4ee9ed67fa85f38da24d51bd7822235a067cd34129940c65224be6a1c5e4"},"schema_version":"1.0"},"canonical_sha256":"78b96187d6c2205f3958b285108867d0dc1ba2a7b424b48f77ae67437252ac23","source":{"kind":"arxiv","id":"2305.12296","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.12296","created_at":"2026-07-05T06:12:51Z"},{"alias_kind":"arxiv_version","alias_value":"2305.12296v2","created_at":"2026-07-05T06:12:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.12296","created_at":"2026-07-05T06:12:51Z"},{"alias_kind":"pith_short_12","alias_value":"PC4WDB6WYIQF","created_at":"2026-07-05T06:12:51Z"},{"alias_kind":"pith_short_16","alias_value":"PC4WDB6WYIQF6OKY","created_at":"2026-07-05T06:12:51Z"},{"alias_kind":"pith_short_8","alias_value":"PC4WDB6W","created_at":"2026-07-05T06:12:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:PC4WDB6WYIQF6OKYWKCRBCDH2D","target":"record","payload":{"canonical_record":{"source":{"id":"2305.12296","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-20T22:27:41Z","cross_cats_sorted":["cs.AI","cs.GR"],"title_canon_sha256":"b984d2c414c10f0a04b2d308943423422decddd9fc5728bfb680d0cf1f1badda","abstract_canon_sha256":"b0ac4ee9ed67fa85f38da24d51bd7822235a067cd34129940c65224be6a1c5e4"},"schema_version":"1.0"},"canonical_sha256":"78b96187d6c2205f3958b285108867d0dc1ba2a7b424b48f77ae67437252ac23","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:12:51.139851Z","signature_b64":"RfC6/bgbKSOtLn0rotPsXk86s6BAjbueVuCt6K2y34mfKTiIeY5oUC4Neg/vvD7pSq8Mk6rWSNu3XJLR2mkFBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"78b96187d6c2205f3958b285108867d0dc1ba2a7b424b48f77ae67437252ac23","last_reissued_at":"2026-07-05T06:12:51.139436Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:12:51.139436Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2305.12296","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:12:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"v8j2C7YZes1A5BmhoMgXQF5ca6CLUGZz781UbE+mkOcLlrcN5Fw85A3OIUZ865kIh82nSLJc/v5xQPltim4WCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T00:25:21.410807Z"},"content_sha256":"37b4c17892a957a500e747b065677b92340ee52c9d7f8bf87bfbaab85468bfa2","schema_version":"1.0","event_id":"sha256:37b4c17892a957a500e747b065677b92340ee52c9d7f8bf87bfbaab85468bfa2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:PC4WDB6WYIQF6OKYWKCRBCDH2D","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PhotoMat: A Material Generator Learned from Single Flash Photos","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.GR"],"primary_cat":"cs.CV","authors_text":"Kalyan Sunkavalli, Milo\\v{s} Ha\\v{s}an, Nima Khademi Kalantari, Paul Guerrero, Valentin Deschaintre, Xilong Zhou, Yannick Hold-Geoffroy","submitted_at":"2023-05-20T22:27:41Z","abstract_excerpt":"Authoring high-quality digital materials is key to realism in 3D rendering. Previous generative models for materials have been trained exclusively on synthetic data; such data is limited in availability and has a visual gap to real materials. We circumvent this limitation by proposing PhotoMat: the first material generator trained exclusively on real photos of material samples captured using a cell phone camera with flash. Supervision on individual material maps is not available in this setting. Instead, we train a generator for a neural material representation that is rendered with a learned "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.12296","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/2305.12296/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":"2026-07-05T06:12:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"43/aviEbSjMQGLRzEIYrDVB6fp67Al9Tk+Gl+vv785VXVub1HEzPWW4W0bYBLIsqWjral+YIOL5zhoXy9FP8Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T00:25:21.411407Z"},"content_sha256":"59c76713d2bcc30e98c7a666718ce70114c4e651261768a8ca42de5d2f9c4ed3","schema_version":"1.0","event_id":"sha256:59c76713d2bcc30e98c7a666718ce70114c4e651261768a8ca42de5d2f9c4ed3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PC4WDB6WYIQF6OKYWKCRBCDH2D/bundle.json","state_url":"https://pith.science/pith/PC4WDB6WYIQF6OKYWKCRBCDH2D/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PC4WDB6WYIQF6OKYWKCRBCDH2D/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":"2026-08-11T00:25:21Z","links":{"resolver":"https://pith.science/pith/PC4WDB6WYIQF6OKYWKCRBCDH2D","bundle":"https://pith.science/pith/PC4WDB6WYIQF6OKYWKCRBCDH2D/bundle.json","state":"https://pith.science/pith/PC4WDB6WYIQF6OKYWKCRBCDH2D/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PC4WDB6WYIQF6OKYWKCRBCDH2D/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:PC4WDB6WYIQF6OKYWKCRBCDH2D","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":"b0ac4ee9ed67fa85f38da24d51bd7822235a067cd34129940c65224be6a1c5e4","cross_cats_sorted":["cs.AI","cs.GR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-20T22:27:41Z","title_canon_sha256":"b984d2c414c10f0a04b2d308943423422decddd9fc5728bfb680d0cf1f1badda"},"schema_version":"1.0","source":{"id":"2305.12296","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.12296","created_at":"2026-07-05T06:12:51Z"},{"alias_kind":"arxiv_version","alias_value":"2305.12296v2","created_at":"2026-07-05T06:12:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.12296","created_at":"2026-07-05T06:12:51Z"},{"alias_kind":"pith_short_12","alias_value":"PC4WDB6WYIQF","created_at":"2026-07-05T06:12:51Z"},{"alias_kind":"pith_short_16","alias_value":"PC4WDB6WYIQF6OKY","created_at":"2026-07-05T06:12:51Z"},{"alias_kind":"pith_short_8","alias_value":"PC4WDB6W","created_at":"2026-07-05T06:12:51Z"}],"graph_snapshots":[{"event_id":"sha256:59c76713d2bcc30e98c7a666718ce70114c4e651261768a8ca42de5d2f9c4ed3","target":"graph","created_at":"2026-07-05T06:12:51Z","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/2305.12296/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Authoring high-quality digital materials is key to realism in 3D rendering. Previous generative models for materials have been trained exclusively on synthetic data; such data is limited in availability and has a visual gap to real materials. We circumvent this limitation by proposing PhotoMat: the first material generator trained exclusively on real photos of material samples captured using a cell phone camera with flash. Supervision on individual material maps is not available in this setting. Instead, we train a generator for a neural material representation that is rendered with a learned ","authors_text":"Kalyan Sunkavalli, Milo\\v{s} Ha\\v{s}an, Nima Khademi Kalantari, Paul Guerrero, Valentin Deschaintre, Xilong Zhou, Yannick Hold-Geoffroy","cross_cats":["cs.AI","cs.GR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-20T22:27:41Z","title":"PhotoMat: A Material Generator Learned from Single Flash Photos"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.12296","kind":"arxiv","version":2},"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":"sha256:37b4c17892a957a500e747b065677b92340ee52c9d7f8bf87bfbaab85468bfa2","target":"record","created_at":"2026-07-05T06:12:51Z","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":"b0ac4ee9ed67fa85f38da24d51bd7822235a067cd34129940c65224be6a1c5e4","cross_cats_sorted":["cs.AI","cs.GR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-20T22:27:41Z","title_canon_sha256":"b984d2c414c10f0a04b2d308943423422decddd9fc5728bfb680d0cf1f1badda"},"schema_version":"1.0","source":{"id":"2305.12296","kind":"arxiv","version":2}},"canonical_sha256":"78b96187d6c2205f3958b285108867d0dc1ba2a7b424b48f77ae67437252ac23","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"78b96187d6c2205f3958b285108867d0dc1ba2a7b424b48f77ae67437252ac23","first_computed_at":"2026-07-05T06:12:51.139436Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:12:51.139436Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"RfC6/bgbKSOtLn0rotPsXk86s6BAjbueVuCt6K2y34mfKTiIeY5oUC4Neg/vvD7pSq8Mk6rWSNu3XJLR2mkFBg==","signature_status":"signed_v1","signed_at":"2026-07-05T06:12:51.139851Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.12296","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:37b4c17892a957a500e747b065677b92340ee52c9d7f8bf87bfbaab85468bfa2","sha256:59c76713d2bcc30e98c7a666718ce70114c4e651261768a8ca42de5d2f9c4ed3"],"state_sha256":"59e4c68439cfbbec7db9564f22ab2e2457c330c7b81d300e24cb856b13c297e8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1WMSzfnJ1WGGjmFd+pKYJLczhOc0EXYU1akjMFgwrTIO/4nFYi0+yx590aBGiHrCyP1UwezMzGuAOHbme3GbAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T00:25:21.415424Z","bundle_sha256":"eadc37473033ad78b09abc8e4ad459688fdcfe4456ec8001e039701c734762e1"}}