{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:YNZXQMXTGH2ZWREBJEZT52GSMU","short_pith_number":"pith:YNZXQMXT","canonical_record":{"source":{"id":"2006.04325","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-06-08T02:30:13Z","cross_cats_sorted":[],"title_canon_sha256":"7b2b93e55c2981a48eefe7c6807c539ca98a7206be178d977f1bc63e46021a4d","abstract_canon_sha256":"811f06949c36df61499337228032f3c0db7b7c2024c3243b922f571e442bfa8f"},"schema_version":"1.0"},"canonical_sha256":"c3737832f331f59b448149333ee8d265243171fc000ab5c6e3f02a712d135f66","source":{"kind":"arxiv","id":"2006.04325","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2006.04325","created_at":"2026-07-05T01:44:48Z"},{"alias_kind":"arxiv_version","alias_value":"2006.04325v2","created_at":"2026-07-05T01:44:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2006.04325","created_at":"2026-07-05T01:44:48Z"},{"alias_kind":"pith_short_12","alias_value":"YNZXQMXTGH2Z","created_at":"2026-07-05T01:44:48Z"},{"alias_kind":"pith_short_16","alias_value":"YNZXQMXTGH2ZWREB","created_at":"2026-07-05T01:44:48Z"},{"alias_kind":"pith_short_8","alias_value":"YNZXQMXT","created_at":"2026-07-05T01:44:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:YNZXQMXTGH2ZWREBJEZT52GSMU","target":"record","payload":{"canonical_record":{"source":{"id":"2006.04325","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-06-08T02:30:13Z","cross_cats_sorted":[],"title_canon_sha256":"7b2b93e55c2981a48eefe7c6807c539ca98a7206be178d977f1bc63e46021a4d","abstract_canon_sha256":"811f06949c36df61499337228032f3c0db7b7c2024c3243b922f571e442bfa8f"},"schema_version":"1.0"},"canonical_sha256":"c3737832f331f59b448149333ee8d265243171fc000ab5c6e3f02a712d135f66","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:44:48.694935Z","signature_b64":"IbS+IU5vKZa+UZZTYp8Pc2GpTJlZBlUIEQcDc6+nym7tPRXBbWoxMBCc6UAsEK8b6AbeArEC23W+fpLSh2r5Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c3737832f331f59b448149333ee8d265243171fc000ab5c6e3f02a712d135f66","last_reissued_at":"2026-07-05T01:44:48.694514Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:44:48.694514Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2006.04325","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":"2026-07-05T01:44:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3NRHwap3OVEBSVdHD06sIOTkdltzBCb6UYkj+64kjy/9yIvg3W7ZYPb5rZSyH9ZIVELmCAZmYx/Gtx8ibbkZAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T03:56:33.898248Z"},"content_sha256":"e13f99f4fb4b0fd3a136b1bf59a9d3fa462bf4fd2523069396133f18181a9582","schema_version":"1.0","event_id":"sha256:e13f99f4fb4b0fd3a136b1bf59a9d3fa462bf4fd2523069396133f18181a9582"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:YNZXQMXTGH2ZWREBJEZT52GSMU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Fully Convolutional Mesh Autoencoder using Efficient Spatially Varying Kernels","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chen Cao, Chenglei Wu, Hao Li, Jason Saragih, Yaser Sheikh, Yi Zhou, Yuting Ye, Zimo Li","submitted_at":"2020-06-08T02:30:13Z","abstract_excerpt":"Learning latent representations of registered meshes is useful for many 3D tasks. Techniques have recently shifted to neural mesh autoencoders. Although they demonstrate higher precision than traditional methods, they remain unable to capture fine-grained deformations. Furthermore, these methods can only be applied to a template-specific surface mesh, and is not applicable to more general meshes, like tetrahedrons and non-manifold meshes. While more general graph convolution methods can be employed, they lack performance in reconstruction precision and require higher memory usage. In this pape"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2006.04325","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/2006.04325/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":"2026-07-05T01:44:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AYmq75Xdo/XAa45HF+CUiMdJn7NKYIWCOPnKbx816y4kssIus891Muz3hWLwuvBhzhha+mHIcQ8yOVXs2ttXAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T03:56:33.898830Z"},"content_sha256":"e9bee6230f630bae6d6ecaff9f72bd24dc73d3989d255a8aabb372656e6b9685","schema_version":"1.0","event_id":"sha256:e9bee6230f630bae6d6ecaff9f72bd24dc73d3989d255a8aabb372656e6b9685"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YNZXQMXTGH2ZWREBJEZT52GSMU/bundle.json","state_url":"https://pith.science/pith/YNZXQMXTGH2ZWREBJEZT52GSMU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YNZXQMXTGH2ZWREBJEZT52GSMU/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":"2026-08-19T03:56:33Z","links":{"resolver":"https://pith.science/pith/YNZXQMXTGH2ZWREBJEZT52GSMU","bundle":"https://pith.science/pith/YNZXQMXTGH2ZWREBJEZT52GSMU/bundle.json","state":"https://pith.science/pith/YNZXQMXTGH2ZWREBJEZT52GSMU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YNZXQMXTGH2ZWREBJEZT52GSMU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:YNZXQMXTGH2ZWREBJEZT52GSMU","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":"811f06949c36df61499337228032f3c0db7b7c2024c3243b922f571e442bfa8f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-06-08T02:30:13Z","title_canon_sha256":"7b2b93e55c2981a48eefe7c6807c539ca98a7206be178d977f1bc63e46021a4d"},"schema_version":"1.0","source":{"id":"2006.04325","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2006.04325","created_at":"2026-07-05T01:44:48Z"},{"alias_kind":"arxiv_version","alias_value":"2006.04325v2","created_at":"2026-07-05T01:44:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2006.04325","created_at":"2026-07-05T01:44:48Z"},{"alias_kind":"pith_short_12","alias_value":"YNZXQMXTGH2Z","created_at":"2026-07-05T01:44:48Z"},{"alias_kind":"pith_short_16","alias_value":"YNZXQMXTGH2ZWREB","created_at":"2026-07-05T01:44:48Z"},{"alias_kind":"pith_short_8","alias_value":"YNZXQMXT","created_at":"2026-07-05T01:44:48Z"}],"graph_snapshots":[{"event_id":"sha256:e9bee6230f630bae6d6ecaff9f72bd24dc73d3989d255a8aabb372656e6b9685","target":"graph","created_at":"2026-07-05T01:44:48Z","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/2006.04325/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Learning latent representations of registered meshes is useful for many 3D tasks. Techniques have recently shifted to neural mesh autoencoders. Although they demonstrate higher precision than traditional methods, they remain unable to capture fine-grained deformations. Furthermore, these methods can only be applied to a template-specific surface mesh, and is not applicable to more general meshes, like tetrahedrons and non-manifold meshes. While more general graph convolution methods can be employed, they lack performance in reconstruction precision and require higher memory usage. In this pape","authors_text":"Chen Cao, Chenglei Wu, Hao Li, Jason Saragih, Yaser Sheikh, Yi Zhou, Yuting Ye, Zimo Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-06-08T02:30:13Z","title":"Fully Convolutional Mesh Autoencoder using Efficient Spatially Varying Kernels"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2006.04325","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:e13f99f4fb4b0fd3a136b1bf59a9d3fa462bf4fd2523069396133f18181a9582","target":"record","created_at":"2026-07-05T01:44:48Z","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":"811f06949c36df61499337228032f3c0db7b7c2024c3243b922f571e442bfa8f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-06-08T02:30:13Z","title_canon_sha256":"7b2b93e55c2981a48eefe7c6807c539ca98a7206be178d977f1bc63e46021a4d"},"schema_version":"1.0","source":{"id":"2006.04325","kind":"arxiv","version":2}},"canonical_sha256":"c3737832f331f59b448149333ee8d265243171fc000ab5c6e3f02a712d135f66","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c3737832f331f59b448149333ee8d265243171fc000ab5c6e3f02a712d135f66","first_computed_at":"2026-07-05T01:44:48.694514Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:44:48.694514Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"IbS+IU5vKZa+UZZTYp8Pc2GpTJlZBlUIEQcDc6+nym7tPRXBbWoxMBCc6UAsEK8b6AbeArEC23W+fpLSh2r5Dg==","signature_status":"signed_v1","signed_at":"2026-07-05T01:44:48.694935Z","signed_message":"canonical_sha256_bytes"},"source_id":"2006.04325","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e13f99f4fb4b0fd3a136b1bf59a9d3fa462bf4fd2523069396133f18181a9582","sha256:e9bee6230f630bae6d6ecaff9f72bd24dc73d3989d255a8aabb372656e6b9685"],"state_sha256":"b7374a852268258bf76470237defbc9785782c2bc911b5dac1fec86680840597"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Y6AfOJkIhFadIAuyfthOUY5RitPmiwUq78liRJKqEKU1nQ3kGeM/5pcpn1psbVr6UiquXwZSjVC58PKacHpQDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T03:56:33.904227Z","bundle_sha256":"6fcb8798f4bf7af135d49fb4bd187f2435450babf7903d84c85d8a112cd060c8"}}