{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:NJV27LOVPKWR5DYHHGDOVRFXNK","short_pith_number":"pith:NJV27LOV","canonical_record":{"source":{"id":"2304.06700","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-13T17:52:29Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"00558365c6c986c047cd7e5f5706b9fb89d055df6f107bfab7e50b120e19db2e","abstract_canon_sha256":"91a4157887f4e7ec5bc721a4d0e8dbe97ecc39bc5d81f4b8a8060e3674164ed8"},"schema_version":"1.0"},"canonical_sha256":"6a6bafadd57aad1e8f073986eac4b76abeaed003708caff673f59d63df92589c","source":{"kind":"arxiv","id":"2304.06700","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.06700","created_at":"2026-07-05T07:05:07Z"},{"alias_kind":"arxiv_version","alias_value":"2304.06700v2","created_at":"2026-07-05T07:05:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.06700","created_at":"2026-07-05T07:05:07Z"},{"alias_kind":"pith_short_12","alias_value":"NJV27LOVPKWR","created_at":"2026-07-05T07:05:07Z"},{"alias_kind":"pith_short_16","alias_value":"NJV27LOVPKWR5DYH","created_at":"2026-07-05T07:05:07Z"},{"alias_kind":"pith_short_8","alias_value":"NJV27LOV","created_at":"2026-07-05T07:05:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:NJV27LOVPKWR5DYHHGDOVRFXNK","target":"record","payload":{"canonical_record":{"source":{"id":"2304.06700","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-13T17:52:29Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"00558365c6c986c047cd7e5f5706b9fb89d055df6f107bfab7e50b120e19db2e","abstract_canon_sha256":"91a4157887f4e7ec5bc721a4d0e8dbe97ecc39bc5d81f4b8a8060e3674164ed8"},"schema_version":"1.0"},"canonical_sha256":"6a6bafadd57aad1e8f073986eac4b76abeaed003708caff673f59d63df92589c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:05:07.719191Z","signature_b64":"qXOSgc7EMnn8Xm34Jpbq2raQof7GelEizhvWHBmSDBwl3a9oz9hwYsDigmrnye9JlrcSVgZsulXv0djhPAwEAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6a6bafadd57aad1e8f073986eac4b76abeaed003708caff673f59d63df92589c","last_reissued_at":"2026-07-05T07:05:07.718636Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:05:07.718636Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2304.06700","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":"2026-07-05T07:05:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uJhdKzdAZrpJqXSWbUprkVtRwlUbnOkmQ24PhzuKm0/nICTcev0dukV6tZRYOfFZ0NekiNE9BGSlGw6F2WiFDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T17:08:51.919397Z"},"content_sha256":"33a2473d47e4d63d722b34f8c53062ac593c1536005dd17578ef0a3c20fc7980","schema_version":"1.0","event_id":"sha256:33a2473d47e4d63d722b34f8c53062ac593c1536005dd17578ef0a3c20fc7980"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:NJV27LOVPKWR5DYHHGDOVRFXNK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Control3Diff: Learning Controllable 3D Diffusion Models from Single-view Images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Baoquan Chen, Jiatao Gu, Josh Susskind, Lingjie Liu, Qingzhe Gao, Shuangfei Zhai","submitted_at":"2023-04-13T17:52:29Z","abstract_excerpt":"Diffusion models have recently become the de-facto approach for generative modeling in the 2D domain. However, extending diffusion models to 3D is challenging due to the difficulties in acquiring 3D ground truth data for training. On the other hand, 3D GANs that integrate implicit 3D representations into GANs have shown remarkable 3D-aware generation when trained only on single-view image datasets. However, 3D GANs do not provide straightforward ways to precisely control image synthesis. To address these challenges, We present Control3Diff, a 3D diffusion model that combines the strengths of d"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.06700","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/2304.06700/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":"2026-07-05T07:05:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"P2Gq1lp+PCrxJH5kSuANyJejIO800952m5XGNGkvH1CxvgBybSmmEdwcHE2SfvPF9k4Zj+yo/7uDFO4+w43TBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T17:08:51.920400Z"},"content_sha256":"d191908d7833aee51c11a125eb5995a435e6b6b90c4f2d737109f9273262d27b","schema_version":"1.0","event_id":"sha256:d191908d7833aee51c11a125eb5995a435e6b6b90c4f2d737109f9273262d27b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NJV27LOVPKWR5DYHHGDOVRFXNK/bundle.json","state_url":"https://pith.science/pith/NJV27LOVPKWR5DYHHGDOVRFXNK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NJV27LOVPKWR5DYHHGDOVRFXNK/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":"2026-08-07T17:08:51Z","links":{"resolver":"https://pith.science/pith/NJV27LOVPKWR5DYHHGDOVRFXNK","bundle":"https://pith.science/pith/NJV27LOVPKWR5DYHHGDOVRFXNK/bundle.json","state":"https://pith.science/pith/NJV27LOVPKWR5DYHHGDOVRFXNK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NJV27LOVPKWR5DYHHGDOVRFXNK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:NJV27LOVPKWR5DYHHGDOVRFXNK","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":"91a4157887f4e7ec5bc721a4d0e8dbe97ecc39bc5d81f4b8a8060e3674164ed8","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-13T17:52:29Z","title_canon_sha256":"00558365c6c986c047cd7e5f5706b9fb89d055df6f107bfab7e50b120e19db2e"},"schema_version":"1.0","source":{"id":"2304.06700","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.06700","created_at":"2026-07-05T07:05:07Z"},{"alias_kind":"arxiv_version","alias_value":"2304.06700v2","created_at":"2026-07-05T07:05:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.06700","created_at":"2026-07-05T07:05:07Z"},{"alias_kind":"pith_short_12","alias_value":"NJV27LOVPKWR","created_at":"2026-07-05T07:05:07Z"},{"alias_kind":"pith_short_16","alias_value":"NJV27LOVPKWR5DYH","created_at":"2026-07-05T07:05:07Z"},{"alias_kind":"pith_short_8","alias_value":"NJV27LOV","created_at":"2026-07-05T07:05:07Z"}],"graph_snapshots":[{"event_id":"sha256:d191908d7833aee51c11a125eb5995a435e6b6b90c4f2d737109f9273262d27b","target":"graph","created_at":"2026-07-05T07:05:07Z","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/2304.06700/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Diffusion models have recently become the de-facto approach for generative modeling in the 2D domain. However, extending diffusion models to 3D is challenging due to the difficulties in acquiring 3D ground truth data for training. On the other hand, 3D GANs that integrate implicit 3D representations into GANs have shown remarkable 3D-aware generation when trained only on single-view image datasets. However, 3D GANs do not provide straightforward ways to precisely control image synthesis. To address these challenges, We present Control3Diff, a 3D diffusion model that combines the strengths of d","authors_text":"Baoquan Chen, Jiatao Gu, Josh Susskind, Lingjie Liu, Qingzhe Gao, Shuangfei Zhai","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-13T17:52:29Z","title":"Control3Diff: Learning Controllable 3D Diffusion Models from Single-view Images"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.06700","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":"sha256:33a2473d47e4d63d722b34f8c53062ac593c1536005dd17578ef0a3c20fc7980","target":"record","created_at":"2026-07-05T07:05:07Z","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":"91a4157887f4e7ec5bc721a4d0e8dbe97ecc39bc5d81f4b8a8060e3674164ed8","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-13T17:52:29Z","title_canon_sha256":"00558365c6c986c047cd7e5f5706b9fb89d055df6f107bfab7e50b120e19db2e"},"schema_version":"1.0","source":{"id":"2304.06700","kind":"arxiv","version":2}},"canonical_sha256":"6a6bafadd57aad1e8f073986eac4b76abeaed003708caff673f59d63df92589c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6a6bafadd57aad1e8f073986eac4b76abeaed003708caff673f59d63df92589c","first_computed_at":"2026-07-05T07:05:07.718636Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:05:07.718636Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qXOSgc7EMnn8Xm34Jpbq2raQof7GelEizhvWHBmSDBwl3a9oz9hwYsDigmrnye9JlrcSVgZsulXv0djhPAwEAg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:05:07.719191Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.06700","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:33a2473d47e4d63d722b34f8c53062ac593c1536005dd17578ef0a3c20fc7980","sha256:d191908d7833aee51c11a125eb5995a435e6b6b90c4f2d737109f9273262d27b"],"state_sha256":"05686760c011d762ad98e50e71a872b41547a74b02c611b2c404879262c8113c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AA9bRnjmv8ctvXODgwTJ6pEuUHPSCH6K7CPlvm//UbWii1gA95EsmHFWIqQI4YHs/e3pwiewoFhaENfKsEtFAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T17:08:51.926639Z","bundle_sha256":"a925f3c7ac96529678dd0ffaf9ba96e982c6c570c60c30698af35d8022c27e59"}}