{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:KRYKXYTNHUK7EGD3IQGKERGQAR","short_pith_number":"pith:KRYKXYTN","canonical_record":{"source":{"id":"2411.16820","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-25T17:08:17Z","cross_cats_sorted":["cs.GR"],"title_canon_sha256":"fd15e647e3aa4205c8c08678e2a51a929a45617cdef6d59dfc2a13d5bbc46215","abstract_canon_sha256":"003f5829e48c2973a826f7fba9f062b8d6b3cb6408b5727d04e27e623087474d"},"schema_version":"1.0"},"canonical_sha256":"5470abe26d3d15f2187b440ca244d0044927cfc47fdf6ec3cab5e8b8b184c769","source":{"kind":"arxiv","id":"2411.16820","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.16820","created_at":"2026-07-05T10:42:39Z"},{"alias_kind":"arxiv_version","alias_value":"2411.16820v3","created_at":"2026-07-05T10:42:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.16820","created_at":"2026-07-05T10:42:39Z"},{"alias_kind":"pith_short_12","alias_value":"KRYKXYTNHUK7","created_at":"2026-07-05T10:42:39Z"},{"alias_kind":"pith_short_16","alias_value":"KRYKXYTNHUK7EGD3","created_at":"2026-07-05T10:42:39Z"},{"alias_kind":"pith_short_8","alias_value":"KRYKXYTN","created_at":"2026-07-05T10:42:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:KRYKXYTNHUK7EGD3IQGKERGQAR","target":"record","payload":{"canonical_record":{"source":{"id":"2411.16820","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-25T17:08:17Z","cross_cats_sorted":["cs.GR"],"title_canon_sha256":"fd15e647e3aa4205c8c08678e2a51a929a45617cdef6d59dfc2a13d5bbc46215","abstract_canon_sha256":"003f5829e48c2973a826f7fba9f062b8d6b3cb6408b5727d04e27e623087474d"},"schema_version":"1.0"},"canonical_sha256":"5470abe26d3d15f2187b440ca244d0044927cfc47fdf6ec3cab5e8b8b184c769","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:42:39.421531Z","signature_b64":"DWjITODUdT+eqdg1GcNrfTZZDGV4enAbkJCgTI1fzcgp6sTzuDQz0f3AWnm4vArlqpN70m0L3bqMxsu+IHD0Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5470abe26d3d15f2187b440ca244d0044927cfc47fdf6ec3cab5e8b8b184c769","last_reissued_at":"2026-07-05T10:42:39.421051Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:42:39.421051Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.16820","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:42:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E9Ej6hzXV1tyheLVAdnPyyrpkC33gnwnxtN78dhMLcqqdTCisnIppnDdXABykicelhTNOaII5fuBsGLV7fkoBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T16:59:48.150923Z"},"content_sha256":"7a63b55ca7d44aa753f2c2f0db27b29e699f9e6a320aa79baa89181f4ca6b8e9","schema_version":"1.0","event_id":"sha256:7a63b55ca7d44aa753f2c2f0db27b29e699f9e6a320aa79baa89181f4ca6b8e9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:KRYKXYTNHUK7EGD3IQGKERGQAR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DetailGen3D: Generative 3D Geometry Enhancement via Data-Dependent Flow","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.GR"],"primary_cat":"cs.CV","authors_text":"Ding Liang, Jingxiang Sun, Ken Deng, Xin Cai, Yangguang Li, Yan-Pei Cao, Yebin Liu, Yuan-Chen Guo, Zi-Xin Zou","submitted_at":"2024-11-25T17:08:17Z","abstract_excerpt":"Modern 3D generation methods can rapidly create shapes from sparse or single views, but their outputs often lack geometric detail due to computational constraints. We present DetailGen3D, a generative approach specifically designed to enhance these generated 3D shapes. Our key insight is to model the coarse-to-fine transformation directly through data-dependent flows in latent space, avoiding the computational overhead of large-scale 3D generative models. We introduce a token matching strategy that ensures accurate spatial correspondence during refinement, enabling local detail synthesis while"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.16820","kind":"arxiv","version":3},"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/2411.16820/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":"2026-07-05T10:42:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zPa3+X385UGJ1pDxG9NP61fqLEUQJy5x1ryut5dscnqd5DpmwkZIcAAyy4U0Bm6cCdbMpIX/Ekn1866NsC3CAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T16:59:48.151432Z"},"content_sha256":"b3e1633f74c3241a710f206b864b4655e71b13a384676697112b1e985032d70b","schema_version":"1.0","event_id":"sha256:b3e1633f74c3241a710f206b864b4655e71b13a384676697112b1e985032d70b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KRYKXYTNHUK7EGD3IQGKERGQAR/bundle.json","state_url":"https://pith.science/pith/KRYKXYTNHUK7EGD3IQGKERGQAR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KRYKXYTNHUK7EGD3IQGKERGQAR/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":"2026-08-08T16:59:48Z","links":{"resolver":"https://pith.science/pith/KRYKXYTNHUK7EGD3IQGKERGQAR","bundle":"https://pith.science/pith/KRYKXYTNHUK7EGD3IQGKERGQAR/bundle.json","state":"https://pith.science/pith/KRYKXYTNHUK7EGD3IQGKERGQAR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KRYKXYTNHUK7EGD3IQGKERGQAR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:KRYKXYTNHUK7EGD3IQGKERGQAR","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":"003f5829e48c2973a826f7fba9f062b8d6b3cb6408b5727d04e27e623087474d","cross_cats_sorted":["cs.GR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-25T17:08:17Z","title_canon_sha256":"fd15e647e3aa4205c8c08678e2a51a929a45617cdef6d59dfc2a13d5bbc46215"},"schema_version":"1.0","source":{"id":"2411.16820","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.16820","created_at":"2026-07-05T10:42:39Z"},{"alias_kind":"arxiv_version","alias_value":"2411.16820v3","created_at":"2026-07-05T10:42:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.16820","created_at":"2026-07-05T10:42:39Z"},{"alias_kind":"pith_short_12","alias_value":"KRYKXYTNHUK7","created_at":"2026-07-05T10:42:39Z"},{"alias_kind":"pith_short_16","alias_value":"KRYKXYTNHUK7EGD3","created_at":"2026-07-05T10:42:39Z"},{"alias_kind":"pith_short_8","alias_value":"KRYKXYTN","created_at":"2026-07-05T10:42:39Z"}],"graph_snapshots":[{"event_id":"sha256:b3e1633f74c3241a710f206b864b4655e71b13a384676697112b1e985032d70b","target":"graph","created_at":"2026-07-05T10:42:39Z","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/2411.16820/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Modern 3D generation methods can rapidly create shapes from sparse or single views, but their outputs often lack geometric detail due to computational constraints. We present DetailGen3D, a generative approach specifically designed to enhance these generated 3D shapes. Our key insight is to model the coarse-to-fine transformation directly through data-dependent flows in latent space, avoiding the computational overhead of large-scale 3D generative models. We introduce a token matching strategy that ensures accurate spatial correspondence during refinement, enabling local detail synthesis while","authors_text":"Ding Liang, Jingxiang Sun, Ken Deng, Xin Cai, Yangguang Li, Yan-Pei Cao, Yebin Liu, Yuan-Chen Guo, Zi-Xin Zou","cross_cats":["cs.GR"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-25T17:08:17Z","title":"DetailGen3D: Generative 3D Geometry Enhancement via Data-Dependent Flow"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.16820","kind":"arxiv","version":3},"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":"sha256:7a63b55ca7d44aa753f2c2f0db27b29e699f9e6a320aa79baa89181f4ca6b8e9","target":"record","created_at":"2026-07-05T10:42:39Z","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":"003f5829e48c2973a826f7fba9f062b8d6b3cb6408b5727d04e27e623087474d","cross_cats_sorted":["cs.GR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-25T17:08:17Z","title_canon_sha256":"fd15e647e3aa4205c8c08678e2a51a929a45617cdef6d59dfc2a13d5bbc46215"},"schema_version":"1.0","source":{"id":"2411.16820","kind":"arxiv","version":3}},"canonical_sha256":"5470abe26d3d15f2187b440ca244d0044927cfc47fdf6ec3cab5e8b8b184c769","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5470abe26d3d15f2187b440ca244d0044927cfc47fdf6ec3cab5e8b8b184c769","first_computed_at":"2026-07-05T10:42:39.421051Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:42:39.421051Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"DWjITODUdT+eqdg1GcNrfTZZDGV4enAbkJCgTI1fzcgp6sTzuDQz0f3AWnm4vArlqpN70m0L3bqMxsu+IHD0Dw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:42:39.421531Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.16820","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7a63b55ca7d44aa753f2c2f0db27b29e699f9e6a320aa79baa89181f4ca6b8e9","sha256:b3e1633f74c3241a710f206b864b4655e71b13a384676697112b1e985032d70b"],"state_sha256":"613ac3bf5a853370eedbf07b3a5c5b7de57dd1c6eb35598813ff051885cd4856"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4xBXLM767olrcLLGlkSWAlUuubxBf3pd1hp14iiSS3zn0f5247yWrOLNma08FvXf13Gkt+0QFSah2JTCTbmdDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T16:59:48.155805Z","bundle_sha256":"3b37df8845ca1f370423be9b5fc29f13c7bae867c779d5a8f8def21c900f663e"}}