{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:G3KSBUBFYOIJ5VI4UTRC3XTZQU","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":"58b97e3baa6a4a1bccaa98321dad532fa194d9cfe48ceed69e5a8b9846665f3e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-10-01T10:20:59Z","title_canon_sha256":"63f92e7011d1ce711f3651aa2d95155dd626cfba510f0b3c22b1ab55da4300ed"},"schema_version":"1.0","source":{"id":"1910.00287","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1910.00287","created_at":"2026-07-05T00:08:44Z"},{"alias_kind":"arxiv_version","alias_value":"1910.00287v1","created_at":"2026-07-05T00:08:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1910.00287","created_at":"2026-07-05T00:08:44Z"},{"alias_kind":"pith_short_12","alias_value":"G3KSBUBFYOIJ","created_at":"2026-07-05T00:08:44Z"},{"alias_kind":"pith_short_16","alias_value":"G3KSBUBFYOIJ5VI4","created_at":"2026-07-05T00:08:44Z"},{"alias_kind":"pith_short_8","alias_value":"G3KSBUBF","created_at":"2026-07-05T00:08:44Z"}],"graph_snapshots":[{"event_id":"sha256:408221272d02986f44efd4afa123e76da520694fa8ae157849961abfc7055325","target":"graph","created_at":"2026-07-05T00:08:44Z","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/1910.00287/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper we present, to the best of our knowledge, the first method to learn a generative model of 3D shapes from natural images in a fully unsupervised way. For example, we do not use any ground truth 3D or 2D annotations, stereo video, and ego-motion during the training. Our approach follows the general strategy of Generative Adversarial Networks, where an image generator network learns to create image samples that are realistic enough to fool a discriminator network into believing that they are natural images. In contrast, in our approach the image generation is split into 2 stages. In","authors_text":"Attila Szab\\'o, Givi Meishvili, Paolo Favaro","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-10-01T10:20:59Z","title":"Unsupervised Generative 3D Shape Learning from Natural Images"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1910.00287","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":"sha256:023c5e17ffb6fe0124309b7fc0e92cd418775da82257368dab2260503b9a3c8f","target":"record","created_at":"2026-07-05T00:08:44Z","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":"58b97e3baa6a4a1bccaa98321dad532fa194d9cfe48ceed69e5a8b9846665f3e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-10-01T10:20:59Z","title_canon_sha256":"63f92e7011d1ce711f3651aa2d95155dd626cfba510f0b3c22b1ab55da4300ed"},"schema_version":"1.0","source":{"id":"1910.00287","kind":"arxiv","version":1}},"canonical_sha256":"36d520d025c3909ed51ca4e22dde7985272e41befe403197493368ad0ae13931","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"36d520d025c3909ed51ca4e22dde7985272e41befe403197493368ad0ae13931","first_computed_at":"2026-07-05T00:08:44.301120Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:08:44.301120Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"xoHnLKYGZzKAamdt+6t9sNsn7QV5eSUYO7YOl1oZomAR7RTDocFzpjjdfVj0SgGOb0tMywk10Tmo5EEATe94Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T00:08:44.301508Z","signed_message":"canonical_sha256_bytes"},"source_id":"1910.00287","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:023c5e17ffb6fe0124309b7fc0e92cd418775da82257368dab2260503b9a3c8f","sha256:408221272d02986f44efd4afa123e76da520694fa8ae157849961abfc7055325"],"state_sha256":"7f47f5f152ca696c3b78233921ff1bfdcdfb30831dcb142a7f75f1998727acfe"}