{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:SCU5OSROU2VHJ4LO6KPN7P3FRD","short_pith_number":"pith:SCU5OSRO","canonical_record":{"source":{"id":"1811.06229","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GR","submitted_at":"2018-11-15T08:28:00Z","cross_cats_sorted":[],"title_canon_sha256":"c426a347347bdeba0bf6c0846d8df79589a24ca368e330bad57b9e89dcf970db","abstract_canon_sha256":"b6b140c000905eec6f96e258f0e914f6b06697dae5c319d9038897c88429626b"},"schema_version":"1.0"},"canonical_sha256":"90a9d74a2ea6aa74f16ef29edfbf6588fb3417fd119950b40a9ca64b5ff263fc","source":{"kind":"arxiv","id":"1811.06229","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.06229","created_at":"2026-05-18T00:00:38Z"},{"alias_kind":"arxiv_version","alias_value":"1811.06229v1","created_at":"2026-05-18T00:00:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.06229","created_at":"2026-05-18T00:00:38Z"},{"alias_kind":"pith_short_12","alias_value":"SCU5OSROU2VH","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_16","alias_value":"SCU5OSROU2VHJ4LO","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_8","alias_value":"SCU5OSRO","created_at":"2026-05-18T12:32:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:SCU5OSROU2VHJ4LO6KPN7P3FRD","target":"record","payload":{"canonical_record":{"source":{"id":"1811.06229","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GR","submitted_at":"2018-11-15T08:28:00Z","cross_cats_sorted":[],"title_canon_sha256":"c426a347347bdeba0bf6c0846d8df79589a24ca368e330bad57b9e89dcf970db","abstract_canon_sha256":"b6b140c000905eec6f96e258f0e914f6b06697dae5c319d9038897c88429626b"},"schema_version":"1.0"},"canonical_sha256":"90a9d74a2ea6aa74f16ef29edfbf6588fb3417fd119950b40a9ca64b5ff263fc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:00:38.297553Z","signature_b64":"JU3+ipLWtJEdfj2JkbgawbIASzxEYrniBa1Eq6fB49LRrsIQNgbMh7vJW3XeZsQ7B/j0FEkwbCLEEs1l03UIBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"90a9d74a2ea6aa74f16ef29edfbf6588fb3417fd119950b40a9ca64b5ff263fc","last_reissued_at":"2026-05-18T00:00:38.297065Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:00:38.297065Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1811.06229","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":"2026-05-18T00:00:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UrjA7gaPKPO1DPopS9Xkc0SjgZdTLhGt82UjP2x4PbqrwL87KaFQomYv7ZkBKmiEBPWoxsXbtYh/r/5zs5wMAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-29T12:28:43.395905Z"},"content_sha256":"d0585206d2f0260286a1beb987544ea139465e7d4784d2122662ae4d2919d2b3","schema_version":"1.0","event_id":"sha256:d0585206d2f0260286a1beb987544ea139465e7d4784d2122662ae4d2919d2b3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:SCU5OSROU2VHJ4LO6KPN7P3FRD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Hair-GANs: Recovering 3D Hair Structure from a Single Image","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.GR","authors_text":"Meng Zhang, Youyi Zheng","submitted_at":"2018-11-15T08:28:00Z","abstract_excerpt":"We introduce Hair-GANs, an architecture of generative adversarial networks, to recover the 3D hair structure from a single image. The goal of our networks is to build a parametric transformation from 2D hair maps to 3D hair structure. The 3D hair structure is represented as a 3D volumetric field which encodes both the occupancy and the orientation information of the hair strands. Given a single hair image, we first align it with a bust model and extract a set of 2D maps encoding the hair orientation information in 2D, along with the bust depth map to feed into our Hair-GANs. With our generator"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.06229","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":""},"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":"2026-05-18T00:00:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Lag2MA86qgnnEi2ZYvXwlFHiUsi8tzzTKLFZsd4jWTkwiDB0C+xS6JJ2CDOwbA8P+wV/xrd2T9m6kzc2gEGzDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-29T12:28:43.396265Z"},"content_sha256":"e3e7011b4b159289ea795961f7758756ce78d805f38cd8a479e8812de537ea74","schema_version":"1.0","event_id":"sha256:e3e7011b4b159289ea795961f7758756ce78d805f38cd8a479e8812de537ea74"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SCU5OSROU2VHJ4LO6KPN7P3FRD/bundle.json","state_url":"https://pith.science/pith/SCU5OSROU2VHJ4LO6KPN7P3FRD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SCU5OSROU2VHJ4LO6KPN7P3FRD/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":"2026-06-29T12:28:43Z","links":{"resolver":"https://pith.science/pith/SCU5OSROU2VHJ4LO6KPN7P3FRD","bundle":"https://pith.science/pith/SCU5OSROU2VHJ4LO6KPN7P3FRD/bundle.json","state":"https://pith.science/pith/SCU5OSROU2VHJ4LO6KPN7P3FRD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SCU5OSROU2VHJ4LO6KPN7P3FRD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:SCU5OSROU2VHJ4LO6KPN7P3FRD","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":"b6b140c000905eec6f96e258f0e914f6b06697dae5c319d9038897c88429626b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GR","submitted_at":"2018-11-15T08:28:00Z","title_canon_sha256":"c426a347347bdeba0bf6c0846d8df79589a24ca368e330bad57b9e89dcf970db"},"schema_version":"1.0","source":{"id":"1811.06229","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.06229","created_at":"2026-05-18T00:00:38Z"},{"alias_kind":"arxiv_version","alias_value":"1811.06229v1","created_at":"2026-05-18T00:00:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.06229","created_at":"2026-05-18T00:00:38Z"},{"alias_kind":"pith_short_12","alias_value":"SCU5OSROU2VH","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_16","alias_value":"SCU5OSROU2VHJ4LO","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_8","alias_value":"SCU5OSRO","created_at":"2026-05-18T12:32:50Z"}],"graph_snapshots":[{"event_id":"sha256:e3e7011b4b159289ea795961f7758756ce78d805f38cd8a479e8812de537ea74","target":"graph","created_at":"2026-05-18T00:00:38Z","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"},"paper":{"abstract_excerpt":"We introduce Hair-GANs, an architecture of generative adversarial networks, to recover the 3D hair structure from a single image. The goal of our networks is to build a parametric transformation from 2D hair maps to 3D hair structure. The 3D hair structure is represented as a 3D volumetric field which encodes both the occupancy and the orientation information of the hair strands. Given a single hair image, we first align it with a bust model and extract a set of 2D maps encoding the hair orientation information in 2D, along with the bust depth map to feed into our Hair-GANs. With our generator","authors_text":"Meng Zhang, Youyi Zheng","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GR","submitted_at":"2018-11-15T08:28:00Z","title":"Hair-GANs: Recovering 3D Hair Structure from a Single Image"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.06229","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:d0585206d2f0260286a1beb987544ea139465e7d4784d2122662ae4d2919d2b3","target":"record","created_at":"2026-05-18T00:00:38Z","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":"b6b140c000905eec6f96e258f0e914f6b06697dae5c319d9038897c88429626b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GR","submitted_at":"2018-11-15T08:28:00Z","title_canon_sha256":"c426a347347bdeba0bf6c0846d8df79589a24ca368e330bad57b9e89dcf970db"},"schema_version":"1.0","source":{"id":"1811.06229","kind":"arxiv","version":1}},"canonical_sha256":"90a9d74a2ea6aa74f16ef29edfbf6588fb3417fd119950b40a9ca64b5ff263fc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"90a9d74a2ea6aa74f16ef29edfbf6588fb3417fd119950b40a9ca64b5ff263fc","first_computed_at":"2026-05-18T00:00:38.297065Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:00:38.297065Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"JU3+ipLWtJEdfj2JkbgawbIASzxEYrniBa1Eq6fB49LRrsIQNgbMh7vJW3XeZsQ7B/j0FEkwbCLEEs1l03UIBg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:00:38.297553Z","signed_message":"canonical_sha256_bytes"},"source_id":"1811.06229","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d0585206d2f0260286a1beb987544ea139465e7d4784d2122662ae4d2919d2b3","sha256:e3e7011b4b159289ea795961f7758756ce78d805f38cd8a479e8812de537ea74"],"state_sha256":"6bb7df0a7ce94f29fc75faa52dd4dca18f85310d0e7695541156cba98b5111f5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/kp6+hT4AGYWCBAuMJPWvKZBk6dIuwSeNki9IxMFrPndffHBb+Wbmh0F7/nSRXkhRR+tqOVAGWOelL7vZ5pDDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-29T12:28:43.398080Z","bundle_sha256":"f1da2ba73d314c61a6cb37e98881c1bbd6611f51b64775edc76f661081ebbd8b"}}