{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:S4BW25GGVS6HP5DL4HQPYIRME2","short_pith_number":"pith:S4BW25GG","canonical_record":{"source":{"id":"2201.02279","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-01-06T23:50:09Z","cross_cats_sorted":[],"title_canon_sha256":"962100e58d5ad184702c07f520e397eb23a6af82cee909ea6e86b96ab20ee8b9","abstract_canon_sha256":"cf2785fc11c9d84fb5942b56b66c5fd836efb219a43efddc4ea6cc6495c78bb7"},"schema_version":"1.0"},"canonical_sha256":"97036d74c6acbc77f46be1e0fc222c26be1267c9ef811d1c8cf2e33bb1168abd","source":{"kind":"arxiv","id":"2201.02279","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2201.02279","created_at":"2026-07-05T05:01:17Z"},{"alias_kind":"arxiv_version","alias_value":"2201.02279v2","created_at":"2026-07-05T05:01:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2201.02279","created_at":"2026-07-05T05:01:17Z"},{"alias_kind":"pith_short_12","alias_value":"S4BW25GGVS6H","created_at":"2026-07-05T05:01:17Z"},{"alias_kind":"pith_short_16","alias_value":"S4BW25GGVS6HP5DL","created_at":"2026-07-05T05:01:17Z"},{"alias_kind":"pith_short_8","alias_value":"S4BW25GG","created_at":"2026-07-05T05:01:17Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:S4BW25GGVS6HP5DL4HQPYIRME2","target":"record","payload":{"canonical_record":{"source":{"id":"2201.02279","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-01-06T23:50:09Z","cross_cats_sorted":[],"title_canon_sha256":"962100e58d5ad184702c07f520e397eb23a6af82cee909ea6e86b96ab20ee8b9","abstract_canon_sha256":"cf2785fc11c9d84fb5942b56b66c5fd836efb219a43efddc4ea6cc6495c78bb7"},"schema_version":"1.0"},"canonical_sha256":"97036d74c6acbc77f46be1e0fc222c26be1267c9ef811d1c8cf2e33bb1168abd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:01:17.985454Z","signature_b64":"DOuMlIE4iNSC4yj6lcd/lVqtRyPOGckhp8V0oQkt/PKl7Ckdn9hCUdKlUtplcAt29PRD6Ll3pw4JgIBMZoNMAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"97036d74c6acbc77f46be1e0fc222c26be1267c9ef811d1c8cf2e33bb1168abd","last_reissued_at":"2026-07-05T05:01:17.985003Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:01:17.985003Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2201.02279","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":"2026-07-05T05:01:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zYTM5PS5xAGjl7+aXGL2Ym3ffDmoPJmkVx3ybPIO8PwkrRn6rk3KQ6JCjdT72hQwa4Soef6vQZUd36GlpIDCBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T16:31:59.349453Z"},"content_sha256":"4e7cb3da5538a3b0cd4f14437184d2874ac93dba85d67aa5d2b4db3d25f45b94","schema_version":"1.0","event_id":"sha256:4e7cb3da5538a3b0cd4f14437184d2874ac93dba85d67aa5d2b4db3d25f45b94"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:S4BW25GGVS6HP5DL4HQPYIRME2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"De-rendering 3D Objects in the Wild","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Christian Rupprecht, Felix Wimbauer, Shangzhe Wu","submitted_at":"2022-01-06T23:50:09Z","abstract_excerpt":"With increasing focus on augmented and virtual reality applications (XR) comes the demand for algorithms that can lift objects from images and videos into representations that are suitable for a wide variety of related 3D tasks. Large-scale deployment of XR devices and applications means that we cannot solely rely on supervised learning, as collecting and annotating data for the unlimited variety of objects in the real world is infeasible. We present a weakly supervised method that is able to decompose a single image of an object into shape (depth and normals), material (albedo, reflectivity a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2201.02279","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/2201.02279/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":"2026-07-05T05:01:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"N5CWHc+/kpUZ/FjR7BFOex9u2SHyw2Lg7Ox32ci9rOCXmLlLWkMm3onvewifPa5xkSsR0NeafzCaEy+eavp7AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T16:31:59.349961Z"},"content_sha256":"53c58e22ee4e486d571eaabd236a2c802791bd572ef4ddfe67e7fe2926c01c39","schema_version":"1.0","event_id":"sha256:53c58e22ee4e486d571eaabd236a2c802791bd572ef4ddfe67e7fe2926c01c39"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/S4BW25GGVS6HP5DL4HQPYIRME2/bundle.json","state_url":"https://pith.science/pith/S4BW25GGVS6HP5DL4HQPYIRME2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/S4BW25GGVS6HP5DL4HQPYIRME2/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":"2026-08-15T16:31:59Z","links":{"resolver":"https://pith.science/pith/S4BW25GGVS6HP5DL4HQPYIRME2","bundle":"https://pith.science/pith/S4BW25GGVS6HP5DL4HQPYIRME2/bundle.json","state":"https://pith.science/pith/S4BW25GGVS6HP5DL4HQPYIRME2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/S4BW25GGVS6HP5DL4HQPYIRME2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:S4BW25GGVS6HP5DL4HQPYIRME2","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":"cf2785fc11c9d84fb5942b56b66c5fd836efb219a43efddc4ea6cc6495c78bb7","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-01-06T23:50:09Z","title_canon_sha256":"962100e58d5ad184702c07f520e397eb23a6af82cee909ea6e86b96ab20ee8b9"},"schema_version":"1.0","source":{"id":"2201.02279","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2201.02279","created_at":"2026-07-05T05:01:17Z"},{"alias_kind":"arxiv_version","alias_value":"2201.02279v2","created_at":"2026-07-05T05:01:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2201.02279","created_at":"2026-07-05T05:01:17Z"},{"alias_kind":"pith_short_12","alias_value":"S4BW25GGVS6H","created_at":"2026-07-05T05:01:17Z"},{"alias_kind":"pith_short_16","alias_value":"S4BW25GGVS6HP5DL","created_at":"2026-07-05T05:01:17Z"},{"alias_kind":"pith_short_8","alias_value":"S4BW25GG","created_at":"2026-07-05T05:01:17Z"}],"graph_snapshots":[{"event_id":"sha256:53c58e22ee4e486d571eaabd236a2c802791bd572ef4ddfe67e7fe2926c01c39","target":"graph","created_at":"2026-07-05T05:01:17Z","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/2201.02279/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"With increasing focus on augmented and virtual reality applications (XR) comes the demand for algorithms that can lift objects from images and videos into representations that are suitable for a wide variety of related 3D tasks. Large-scale deployment of XR devices and applications means that we cannot solely rely on supervised learning, as collecting and annotating data for the unlimited variety of objects in the real world is infeasible. We present a weakly supervised method that is able to decompose a single image of an object into shape (depth and normals), material (albedo, reflectivity a","authors_text":"Christian Rupprecht, Felix Wimbauer, Shangzhe Wu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-01-06T23:50:09Z","title":"De-rendering 3D Objects in the Wild"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2201.02279","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":"sha256:4e7cb3da5538a3b0cd4f14437184d2874ac93dba85d67aa5d2b4db3d25f45b94","target":"record","created_at":"2026-07-05T05:01:17Z","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":"cf2785fc11c9d84fb5942b56b66c5fd836efb219a43efddc4ea6cc6495c78bb7","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-01-06T23:50:09Z","title_canon_sha256":"962100e58d5ad184702c07f520e397eb23a6af82cee909ea6e86b96ab20ee8b9"},"schema_version":"1.0","source":{"id":"2201.02279","kind":"arxiv","version":2}},"canonical_sha256":"97036d74c6acbc77f46be1e0fc222c26be1267c9ef811d1c8cf2e33bb1168abd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"97036d74c6acbc77f46be1e0fc222c26be1267c9ef811d1c8cf2e33bb1168abd","first_computed_at":"2026-07-05T05:01:17.985003Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:01:17.985003Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"DOuMlIE4iNSC4yj6lcd/lVqtRyPOGckhp8V0oQkt/PKl7Ckdn9hCUdKlUtplcAt29PRD6Ll3pw4JgIBMZoNMAg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:01:17.985454Z","signed_message":"canonical_sha256_bytes"},"source_id":"2201.02279","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4e7cb3da5538a3b0cd4f14437184d2874ac93dba85d67aa5d2b4db3d25f45b94","sha256:53c58e22ee4e486d571eaabd236a2c802791bd572ef4ddfe67e7fe2926c01c39"],"state_sha256":"69d3fd91e28448f5fd1e79cd300ca05d2b8d17e6e9a91166d9286addc5eb65c8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4eoEEMj80wm/zhOqaUNDqDjb49qXEjXPpiBEGj4mU+jDVTjYStu20QXtomd2bM9LtIp/oP84rugTQW7emYthDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-15T16:31:59.360990Z","bundle_sha256":"17e6818882acd73fffb680fdc6fb483234b4959cd3c3f2a14889bfc609814eed"}}