{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:57ERPCCCXSEQ6KO4ULOLJI7FFG","short_pith_number":"pith:57ERPCCC","canonical_record":{"source":{"id":"2303.01416","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-02T17:06:57Z","cross_cats_sorted":["cs.AI","cs.GR"],"title_canon_sha256":"4f28229d83e04c7dbf4ea57db138b6676a7f8bf63f2a12f1ecb0e3466ff99d52","abstract_canon_sha256":"f14d2365da7635ceb1f2409db28a27c60b144f2a5fe290666d684f27a1be122c"},"schema_version":"1.0"},"canonical_sha256":"efc9178842bc890f29dca2dcb4a3e5298c799912a27217bf060f8ab4d340984c","source":{"kind":"arxiv","id":"2303.01416","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.01416","created_at":"2026-07-05T05:47:30Z"},{"alias_kind":"arxiv_version","alias_value":"2303.01416v1","created_at":"2026-07-05T05:47:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.01416","created_at":"2026-07-05T05:47:30Z"},{"alias_kind":"pith_short_12","alias_value":"57ERPCCCXSEQ","created_at":"2026-07-05T05:47:30Z"},{"alias_kind":"pith_short_16","alias_value":"57ERPCCCXSEQ6KO4","created_at":"2026-07-05T05:47:30Z"},{"alias_kind":"pith_short_8","alias_value":"57ERPCCC","created_at":"2026-07-05T05:47:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:57ERPCCCXSEQ6KO4ULOLJI7FFG","target":"record","payload":{"canonical_record":{"source":{"id":"2303.01416","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-02T17:06:57Z","cross_cats_sorted":["cs.AI","cs.GR"],"title_canon_sha256":"4f28229d83e04c7dbf4ea57db138b6676a7f8bf63f2a12f1ecb0e3466ff99d52","abstract_canon_sha256":"f14d2365da7635ceb1f2409db28a27c60b144f2a5fe290666d684f27a1be122c"},"schema_version":"1.0"},"canonical_sha256":"efc9178842bc890f29dca2dcb4a3e5298c799912a27217bf060f8ab4d340984c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:47:30.615064Z","signature_b64":"VGqzrNcM8jJ4grKGuWogcyJWVUhN2ctBWolClTC3fyWt6sKtceKgv1A6ZETtnkFV9Arxldsf5IWXaIak3+W7Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"efc9178842bc890f29dca2dcb4a3e5298c799912a27217bf060f8ab4d340984c","last_reissued_at":"2026-07-05T05:47:30.614368Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:47:30.614368Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2303.01416","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":"2026-07-05T05:47:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"s/Bse/oqlRN5DbSAJgbDj2Lw3mg71GzRoqSIALLq6IO2zuvp0qvuB9/02RP5nzYRl32Hj4TuuUF6rbxcqHHDBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T00:12:20.412674Z"},"content_sha256":"4121b3cf1d49cbff37edf674c2d36a54ba0ce0a451ff202631de04a0e5784f54","schema_version":"1.0","event_id":"sha256:4121b3cf1d49cbff37edf674c2d36a54ba0ce0a451ff202631de04a0e5784f54"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:57ERPCCCXSEQ6KO4ULOLJI7FFG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"3D generation on ImageNet","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.GR"],"primary_cat":"cs.CV","authors_text":"Aliaksandr Siarohin, Hsin-Ying Lee, Ivan Skorokhodov, Jian Ren, Peter Wonka, Sergey Tulyakov, Yinghao Xu","submitted_at":"2023-03-02T17:06:57Z","abstract_excerpt":"Existing 3D-from-2D generators are typically designed for well-curated single-category datasets, where all the objects have (approximately) the same scale, 3D location, and orientation, and the camera always points to the center of the scene. This makes them inapplicable to diverse, in-the-wild datasets of non-alignable scenes rendered from arbitrary camera poses. In this work, we develop a 3D generator with Generic Priors (3DGP): a 3D synthesis framework with more general assumptions about the training data, and show that it scales to very challenging datasets, like ImageNet. Our model is bas"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.01416","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/2303.01416/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":"2026-07-05T05:47:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7u3KyqN5+2oOQqQp+36rINRHjdye4V1ActCi+RwiU+qbag5NIhsCWH8uQk3zbc9CaDAV0G51rfiOO0d3p65UAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T00:12:20.413238Z"},"content_sha256":"7ee2d5ad60f77ee15bad8368b198e0814fd3c8a11fb4d4328f7f04aa5e67d9c0","schema_version":"1.0","event_id":"sha256:7ee2d5ad60f77ee15bad8368b198e0814fd3c8a11fb4d4328f7f04aa5e67d9c0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/57ERPCCCXSEQ6KO4ULOLJI7FFG/bundle.json","state_url":"https://pith.science/pith/57ERPCCCXSEQ6KO4ULOLJI7FFG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/57ERPCCCXSEQ6KO4ULOLJI7FFG/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":"2026-08-07T00:12:20Z","links":{"resolver":"https://pith.science/pith/57ERPCCCXSEQ6KO4ULOLJI7FFG","bundle":"https://pith.science/pith/57ERPCCCXSEQ6KO4ULOLJI7FFG/bundle.json","state":"https://pith.science/pith/57ERPCCCXSEQ6KO4ULOLJI7FFG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/57ERPCCCXSEQ6KO4ULOLJI7FFG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:57ERPCCCXSEQ6KO4ULOLJI7FFG","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":"f14d2365da7635ceb1f2409db28a27c60b144f2a5fe290666d684f27a1be122c","cross_cats_sorted":["cs.AI","cs.GR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-02T17:06:57Z","title_canon_sha256":"4f28229d83e04c7dbf4ea57db138b6676a7f8bf63f2a12f1ecb0e3466ff99d52"},"schema_version":"1.0","source":{"id":"2303.01416","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.01416","created_at":"2026-07-05T05:47:30Z"},{"alias_kind":"arxiv_version","alias_value":"2303.01416v1","created_at":"2026-07-05T05:47:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.01416","created_at":"2026-07-05T05:47:30Z"},{"alias_kind":"pith_short_12","alias_value":"57ERPCCCXSEQ","created_at":"2026-07-05T05:47:30Z"},{"alias_kind":"pith_short_16","alias_value":"57ERPCCCXSEQ6KO4","created_at":"2026-07-05T05:47:30Z"},{"alias_kind":"pith_short_8","alias_value":"57ERPCCC","created_at":"2026-07-05T05:47:30Z"}],"graph_snapshots":[{"event_id":"sha256:7ee2d5ad60f77ee15bad8368b198e0814fd3c8a11fb4d4328f7f04aa5e67d9c0","target":"graph","created_at":"2026-07-05T05:47:30Z","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/2303.01416/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Existing 3D-from-2D generators are typically designed for well-curated single-category datasets, where all the objects have (approximately) the same scale, 3D location, and orientation, and the camera always points to the center of the scene. This makes them inapplicable to diverse, in-the-wild datasets of non-alignable scenes rendered from arbitrary camera poses. In this work, we develop a 3D generator with Generic Priors (3DGP): a 3D synthesis framework with more general assumptions about the training data, and show that it scales to very challenging datasets, like ImageNet. Our model is bas","authors_text":"Aliaksandr Siarohin, Hsin-Ying Lee, Ivan Skorokhodov, Jian Ren, Peter Wonka, Sergey Tulyakov, Yinghao Xu","cross_cats":["cs.AI","cs.GR"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-02T17:06:57Z","title":"3D generation on ImageNet"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.01416","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":"sha256:4121b3cf1d49cbff37edf674c2d36a54ba0ce0a451ff202631de04a0e5784f54","target":"record","created_at":"2026-07-05T05:47:30Z","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":"f14d2365da7635ceb1f2409db28a27c60b144f2a5fe290666d684f27a1be122c","cross_cats_sorted":["cs.AI","cs.GR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-02T17:06:57Z","title_canon_sha256":"4f28229d83e04c7dbf4ea57db138b6676a7f8bf63f2a12f1ecb0e3466ff99d52"},"schema_version":"1.0","source":{"id":"2303.01416","kind":"arxiv","version":1}},"canonical_sha256":"efc9178842bc890f29dca2dcb4a3e5298c799912a27217bf060f8ab4d340984c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"efc9178842bc890f29dca2dcb4a3e5298c799912a27217bf060f8ab4d340984c","first_computed_at":"2026-07-05T05:47:30.614368Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:47:30.614368Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VGqzrNcM8jJ4grKGuWogcyJWVUhN2ctBWolClTC3fyWt6sKtceKgv1A6ZETtnkFV9Arxldsf5IWXaIak3+W7Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T05:47:30.615064Z","signed_message":"canonical_sha256_bytes"},"source_id":"2303.01416","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4121b3cf1d49cbff37edf674c2d36a54ba0ce0a451ff202631de04a0e5784f54","sha256:7ee2d5ad60f77ee15bad8368b198e0814fd3c8a11fb4d4328f7f04aa5e67d9c0"],"state_sha256":"3abbb04a33eb56ef660e6b9d38a2f23180f8cd18fca82489a619a655410feb15"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qNy33l8mg54diOWfG2VuCpYXdKX1LQ37KKzoVMaV9MzUP8beUB6KFv1hDq8tNbH1r0fszsFjiJiNCQqJMgdwDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T00:12:20.418865Z","bundle_sha256":"0f26e1cd751d2704f7f234db4e8a5a36d54c9627db42ff9c8894577cce94da86"}}