{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:HFHQ4VIYVDRSBXDZDQZYY2PAOJ","short_pith_number":"pith:HFHQ4VIY","canonical_record":{"source":{"id":"2311.16918","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-28T16:22:33Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"32c426a30b45b591b1a95e04df4453441b4440cd55bf7a40e1fa8617fd8c6216","abstract_canon_sha256":"fa8104ad8f182aa4f20a7fb333a7b5844805a7e2bb4236e18f2c630ce05a399e"},"schema_version":"1.0"},"canonical_sha256":"394f0e5518a8e320dc791c338c69e0725c7a689e9b23c1d722ccb2f23b55335b","source":{"kind":"arxiv","id":"2311.16918","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.16918","created_at":"2026-07-05T07:27:53Z"},{"alias_kind":"arxiv_version","alias_value":"2311.16918v2","created_at":"2026-07-05T07:27:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.16918","created_at":"2026-07-05T07:27:53Z"},{"alias_kind":"pith_short_12","alias_value":"HFHQ4VIYVDRS","created_at":"2026-07-05T07:27:53Z"},{"alias_kind":"pith_short_16","alias_value":"HFHQ4VIYVDRSBXDZ","created_at":"2026-07-05T07:27:53Z"},{"alias_kind":"pith_short_8","alias_value":"HFHQ4VIY","created_at":"2026-07-05T07:27:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:HFHQ4VIYVDRSBXDZDQZYY2PAOJ","target":"record","payload":{"canonical_record":{"source":{"id":"2311.16918","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-28T16:22:33Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"32c426a30b45b591b1a95e04df4453441b4440cd55bf7a40e1fa8617fd8c6216","abstract_canon_sha256":"fa8104ad8f182aa4f20a7fb333a7b5844805a7e2bb4236e18f2c630ce05a399e"},"schema_version":"1.0"},"canonical_sha256":"394f0e5518a8e320dc791c338c69e0725c7a689e9b23c1d722ccb2f23b55335b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:27:53.056424Z","signature_b64":"tA7QECdlBVp5roFwhR6L1YYjWHqGWVgWCp8UVRq2IF5uvM/FedLY4wm4/sJlN6/XTB4g8N/TBtqOrrqX2SC7Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"394f0e5518a8e320dc791c338c69e0725c7a689e9b23c1d722ccb2f23b55335b","last_reissued_at":"2026-07-05T07:27:53.055893Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:27:53.055893Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2311.16918","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":"2026-07-05T07:27:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UkAp3sdUlX1NW9XgLnMzN662Heyerg64k73o5qd26quhPhfFclCVu+ll+/hr7tqDjFpvCVvvk5RqXBUZS08ADA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T04:14:56.622697Z"},"content_sha256":"b2aabb89a1c809b6e79c81a2322b4262c694837583c84343949de7fc4697e1ca","schema_version":"1.0","event_id":"sha256:b2aabb89a1c809b6e79c81a2322b4262c694837583c84343949de7fc4697e1ca"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:HFHQ4VIYVDRSBXDZDQZYY2PAOJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"RichDreamer: A Generalizable Normal-Depth Diffusion Model for Detail Richness in Text-to-3D","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Guanying Chen, Liefeng Bo, Lingteng Qiu, Mutian Xu, Qi Zuo, Weihao Yuan, Xiaodong Gu, Xiaoguang Han, Yushuang Wu, Zilong Dong","submitted_at":"2023-11-28T16:22:33Z","abstract_excerpt":"Lifting 2D diffusion for 3D generation is a challenging problem due to the lack of geometric prior and the complex entanglement of materials and lighting in natural images. Existing methods have shown promise by first creating the geometry through score-distillation sampling (SDS) applied to rendered surface normals, followed by appearance modeling. However, relying on a 2D RGB diffusion model to optimize surface normals is suboptimal due to the distribution discrepancy between natural images and normals maps, leading to instability in optimization. In this paper, recognizing that the normal a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.16918","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/2311.16918/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":"2026-07-05T07:27:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xpDNt4hz95P/QD1BsYHaICbv9WGnzjijCeiGSZERCi+kjhUohDXRxgmaBae5TJU4zSBjsEFY2kYXOuJNsz8tCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T04:14:56.623083Z"},"content_sha256":"e567d672deb4628a4f827f8f777362d38ca2dce2957dd9cecfbbf46c2c5462bb","schema_version":"1.0","event_id":"sha256:e567d672deb4628a4f827f8f777362d38ca2dce2957dd9cecfbbf46c2c5462bb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HFHQ4VIYVDRSBXDZDQZYY2PAOJ/bundle.json","state_url":"https://pith.science/pith/HFHQ4VIYVDRSBXDZDQZYY2PAOJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HFHQ4VIYVDRSBXDZDQZYY2PAOJ/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":"2026-08-19T04:14:56Z","links":{"resolver":"https://pith.science/pith/HFHQ4VIYVDRSBXDZDQZYY2PAOJ","bundle":"https://pith.science/pith/HFHQ4VIYVDRSBXDZDQZYY2PAOJ/bundle.json","state":"https://pith.science/pith/HFHQ4VIYVDRSBXDZDQZYY2PAOJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HFHQ4VIYVDRSBXDZDQZYY2PAOJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:HFHQ4VIYVDRSBXDZDQZYY2PAOJ","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":"fa8104ad8f182aa4f20a7fb333a7b5844805a7e2bb4236e18f2c630ce05a399e","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-28T16:22:33Z","title_canon_sha256":"32c426a30b45b591b1a95e04df4453441b4440cd55bf7a40e1fa8617fd8c6216"},"schema_version":"1.0","source":{"id":"2311.16918","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.16918","created_at":"2026-07-05T07:27:53Z"},{"alias_kind":"arxiv_version","alias_value":"2311.16918v2","created_at":"2026-07-05T07:27:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.16918","created_at":"2026-07-05T07:27:53Z"},{"alias_kind":"pith_short_12","alias_value":"HFHQ4VIYVDRS","created_at":"2026-07-05T07:27:53Z"},{"alias_kind":"pith_short_16","alias_value":"HFHQ4VIYVDRSBXDZ","created_at":"2026-07-05T07:27:53Z"},{"alias_kind":"pith_short_8","alias_value":"HFHQ4VIY","created_at":"2026-07-05T07:27:53Z"}],"graph_snapshots":[{"event_id":"sha256:e567d672deb4628a4f827f8f777362d38ca2dce2957dd9cecfbbf46c2c5462bb","target":"graph","created_at":"2026-07-05T07:27:53Z","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/2311.16918/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Lifting 2D diffusion for 3D generation is a challenging problem due to the lack of geometric prior and the complex entanglement of materials and lighting in natural images. Existing methods have shown promise by first creating the geometry through score-distillation sampling (SDS) applied to rendered surface normals, followed by appearance modeling. However, relying on a 2D RGB diffusion model to optimize surface normals is suboptimal due to the distribution discrepancy between natural images and normals maps, leading to instability in optimization. In this paper, recognizing that the normal a","authors_text":"Guanying Chen, Liefeng Bo, Lingteng Qiu, Mutian Xu, Qi Zuo, Weihao Yuan, Xiaodong Gu, Xiaoguang Han, Yushuang Wu, Zilong Dong","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-28T16:22:33Z","title":"RichDreamer: A Generalizable Normal-Depth Diffusion Model for Detail Richness in Text-to-3D"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.16918","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:b2aabb89a1c809b6e79c81a2322b4262c694837583c84343949de7fc4697e1ca","target":"record","created_at":"2026-07-05T07:27:53Z","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":"fa8104ad8f182aa4f20a7fb333a7b5844805a7e2bb4236e18f2c630ce05a399e","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-28T16:22:33Z","title_canon_sha256":"32c426a30b45b591b1a95e04df4453441b4440cd55bf7a40e1fa8617fd8c6216"},"schema_version":"1.0","source":{"id":"2311.16918","kind":"arxiv","version":2}},"canonical_sha256":"394f0e5518a8e320dc791c338c69e0725c7a689e9b23c1d722ccb2f23b55335b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"394f0e5518a8e320dc791c338c69e0725c7a689e9b23c1d722ccb2f23b55335b","first_computed_at":"2026-07-05T07:27:53.055893Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:27:53.055893Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tA7QECdlBVp5roFwhR6L1YYjWHqGWVgWCp8UVRq2IF5uvM/FedLY4wm4/sJlN6/XTB4g8N/TBtqOrrqX2SC7Bw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:27:53.056424Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.16918","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b2aabb89a1c809b6e79c81a2322b4262c694837583c84343949de7fc4697e1ca","sha256:e567d672deb4628a4f827f8f777362d38ca2dce2957dd9cecfbbf46c2c5462bb"],"state_sha256":"6b857620c1cbae38de7607e39cb768d44c5a0c1a7c22612270b9c44933963238"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iMIikk0IAtXQq+VQg8C/HgPwYHfV8lmIRlGDC9cKkHrKKzSTynBuCAVyFWqPARUpSkO9U1SEfS0HN37LcD9eDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T04:14:56.625541Z","bundle_sha256":"ff44d4cf97ebce0077e4aef8fbb962c711ce6b1df5eb14ed8d0d69e06dfec2d3"}}