{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:QYWZXLTYRDGEYPAHOT433GPQ43","short_pith_number":"pith:QYWZXLTY","canonical_record":{"source":{"id":"1811.10720","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-26T22:24:25Z","cross_cats_sorted":[],"title_canon_sha256":"e56a8a7b0445a1176f989a4d40e96b7edcaf602de3e5c59c7ab9a856ab96e173","abstract_canon_sha256":"c88f9c14aee115bc0ce935927d9110d2432865421ed6bdc1aaf390262f592859"},"schema_version":"1.0"},"canonical_sha256":"862d9bae7888cc4c3c0774f9bd99f0e6c1310f30c55b4c9dbd134bc343ee4a98","source":{"kind":"arxiv","id":"1811.10720","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.10720","created_at":"2026-07-05T00:33:33Z"},{"alias_kind":"arxiv_version","alias_value":"1811.10720v2","created_at":"2026-07-05T00:33:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.10720","created_at":"2026-07-05T00:33:33Z"},{"alias_kind":"pith_short_12","alias_value":"QYWZXLTYRDGE","created_at":"2026-07-05T00:33:33Z"},{"alias_kind":"pith_short_16","alias_value":"QYWZXLTYRDGEYPAH","created_at":"2026-07-05T00:33:33Z"},{"alias_kind":"pith_short_8","alias_value":"QYWZXLTY","created_at":"2026-07-05T00:33:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:QYWZXLTYRDGEYPAHOT433GPQ43","target":"record","payload":{"canonical_record":{"source":{"id":"1811.10720","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-26T22:24:25Z","cross_cats_sorted":[],"title_canon_sha256":"e56a8a7b0445a1176f989a4d40e96b7edcaf602de3e5c59c7ab9a856ab96e173","abstract_canon_sha256":"c88f9c14aee115bc0ce935927d9110d2432865421ed6bdc1aaf390262f592859"},"schema_version":"1.0"},"canonical_sha256":"862d9bae7888cc4c3c0774f9bd99f0e6c1310f30c55b4c9dbd134bc343ee4a98","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:33:33.020176Z","signature_b64":"+nyZ+bXjEz/iBC/Xqg/PuBbCGvTOt33hmP3l3paQXuZcmfbbV1m6Sj/1ZbJfkm1K4FvH8SBdw3zqCFb6pg7zCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"862d9bae7888cc4c3c0774f9bd99f0e6c1310f30c55b4c9dbd134bc343ee4a98","last_reissued_at":"2026-07-05T00:33:33.019814Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:33:33.019814Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1811.10720","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":"2026-07-05T00:33:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rAF4kLzaGJyoypDxQuUr0WPj9aGHReAdFaihEDiaZWI5Iiy8iyIoeUHFybX6n3T/1M/xBOD6PN8OeGpN0uBRAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T04:36:46.737538Z"},"content_sha256":"4e7ded23f36146c392132c51de5f39971edbca18bf5056c0e7709898fbc3b943","schema_version":"1.0","event_id":"sha256:4e7ded23f36146c392132c51de5f39971edbca18bf5056c0e7709898fbc3b943"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:QYWZXLTYRDGEYPAHOT433GPQ43","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"IGNOR: Image-guided Neural Object Rendering","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Christian Theobalt, Justus Thies, Marc Stamminger, Matthias Nie{\\ss}ner, Michael Zollh\\\"ofer","submitted_at":"2018-11-26T22:24:25Z","abstract_excerpt":"We propose a learned image-guided rendering technique that combines the benefits of image-based rendering and GAN-based image synthesis. The goal of our method is to generate photo-realistic re-renderings of reconstructed objects for virtual and augmented reality applications (e.g., virtual showrooms, virtual tours \\& sightseeing, the digital inspection of historical artifacts). A core component of our work is the handling of view-dependent effects. Specifically, we directly train an object-specific deep neural network to synthesize the view-dependent appearance of an object. As input data we "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.10720","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/1811.10720/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":"2026-07-05T00:33:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jMtaGmEpsuuo8OEeUjAoSBxWQuK9Pci7hfjuZ9lqDgYjmUPcyEEZY19Ivg00pKGSeHUquBcsEem+M56fj9f8Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T04:36:46.738036Z"},"content_sha256":"7136c32e6a4de32bfca685a7f8408bb37061a6c2bcadd9165b3fb24c6c515571","schema_version":"1.0","event_id":"sha256:7136c32e6a4de32bfca685a7f8408bb37061a6c2bcadd9165b3fb24c6c515571"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QYWZXLTYRDGEYPAHOT433GPQ43/bundle.json","state_url":"https://pith.science/pith/QYWZXLTYRDGEYPAHOT433GPQ43/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QYWZXLTYRDGEYPAHOT433GPQ43/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":"2026-08-17T04:36:46Z","links":{"resolver":"https://pith.science/pith/QYWZXLTYRDGEYPAHOT433GPQ43","bundle":"https://pith.science/pith/QYWZXLTYRDGEYPAHOT433GPQ43/bundle.json","state":"https://pith.science/pith/QYWZXLTYRDGEYPAHOT433GPQ43/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QYWZXLTYRDGEYPAHOT433GPQ43/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:QYWZXLTYRDGEYPAHOT433GPQ43","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":"c88f9c14aee115bc0ce935927d9110d2432865421ed6bdc1aaf390262f592859","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-26T22:24:25Z","title_canon_sha256":"e56a8a7b0445a1176f989a4d40e96b7edcaf602de3e5c59c7ab9a856ab96e173"},"schema_version":"1.0","source":{"id":"1811.10720","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.10720","created_at":"2026-07-05T00:33:33Z"},{"alias_kind":"arxiv_version","alias_value":"1811.10720v2","created_at":"2026-07-05T00:33:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.10720","created_at":"2026-07-05T00:33:33Z"},{"alias_kind":"pith_short_12","alias_value":"QYWZXLTYRDGE","created_at":"2026-07-05T00:33:33Z"},{"alias_kind":"pith_short_16","alias_value":"QYWZXLTYRDGEYPAH","created_at":"2026-07-05T00:33:33Z"},{"alias_kind":"pith_short_8","alias_value":"QYWZXLTY","created_at":"2026-07-05T00:33:33Z"}],"graph_snapshots":[{"event_id":"sha256:7136c32e6a4de32bfca685a7f8408bb37061a6c2bcadd9165b3fb24c6c515571","target":"graph","created_at":"2026-07-05T00:33:33Z","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/1811.10720/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We propose a learned image-guided rendering technique that combines the benefits of image-based rendering and GAN-based image synthesis. The goal of our method is to generate photo-realistic re-renderings of reconstructed objects for virtual and augmented reality applications (e.g., virtual showrooms, virtual tours \\& sightseeing, the digital inspection of historical artifacts). A core component of our work is the handling of view-dependent effects. Specifically, we directly train an object-specific deep neural network to synthesize the view-dependent appearance of an object. As input data we ","authors_text":"Christian Theobalt, Justus Thies, Marc Stamminger, Matthias Nie{\\ss}ner, Michael Zollh\\\"ofer","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-26T22:24:25Z","title":"IGNOR: Image-guided Neural Object Rendering"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.10720","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":"sha256:4e7ded23f36146c392132c51de5f39971edbca18bf5056c0e7709898fbc3b943","target":"record","created_at":"2026-07-05T00:33:33Z","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":"c88f9c14aee115bc0ce935927d9110d2432865421ed6bdc1aaf390262f592859","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-26T22:24:25Z","title_canon_sha256":"e56a8a7b0445a1176f989a4d40e96b7edcaf602de3e5c59c7ab9a856ab96e173"},"schema_version":"1.0","source":{"id":"1811.10720","kind":"arxiv","version":2}},"canonical_sha256":"862d9bae7888cc4c3c0774f9bd99f0e6c1310f30c55b4c9dbd134bc343ee4a98","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"862d9bae7888cc4c3c0774f9bd99f0e6c1310f30c55b4c9dbd134bc343ee4a98","first_computed_at":"2026-07-05T00:33:33.019814Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:33:33.019814Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+nyZ+bXjEz/iBC/Xqg/PuBbCGvTOt33hmP3l3paQXuZcmfbbV1m6Sj/1ZbJfkm1K4FvH8SBdw3zqCFb6pg7zCg==","signature_status":"signed_v1","signed_at":"2026-07-05T00:33:33.020176Z","signed_message":"canonical_sha256_bytes"},"source_id":"1811.10720","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4e7ded23f36146c392132c51de5f39971edbca18bf5056c0e7709898fbc3b943","sha256:7136c32e6a4de32bfca685a7f8408bb37061a6c2bcadd9165b3fb24c6c515571"],"state_sha256":"2c5e4dfb7620423d51cac3f758e241893834597c5543ef95a9243cefa1c2060c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZsLraXsRr+xkwfFLGX6A79B16NQouIb3xyXzLYaBFz5iC8evQ5VNJzw9K2P3pbEBZC5IY/VEuux2fWz5A4XUBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T04:36:46.742716Z","bundle_sha256":"ca3bbbab069f7d57d7f15e58864de86063257776077c1a7ec650228e2a2433cd"}}