{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:Y7ILES3IAUWARLUAV6NZFGRBTD","short_pith_number":"pith:Y7ILES3I","canonical_record":{"source":{"id":"1711.06363","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-17T00:58:53Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"f4f2c1f077cdbfa1c5f80ba3bef583723f776c205ba92c8a28b18116ab4ef7af","abstract_canon_sha256":"30017b68867a74e444e11522f06ca85402657066a49d0b91ab151ef3db17d439"},"schema_version":"1.0"},"canonical_sha256":"c7d0b24b68052c08ae80af9b929a2198c858d2cadd611d29738caa9bbd44347f","source":{"kind":"arxiv","id":"1711.06363","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.06363","created_at":"2026-05-18T00:21:34Z"},{"alias_kind":"arxiv_version","alias_value":"1711.06363v2","created_at":"2026-05-18T00:21:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.06363","created_at":"2026-05-18T00:21:34Z"},{"alias_kind":"pith_short_12","alias_value":"Y7ILES3IAUWA","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_16","alias_value":"Y7ILES3IAUWARLUA","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_8","alias_value":"Y7ILES3I","created_at":"2026-05-18T12:31:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:Y7ILES3IAUWARLUAV6NZFGRBTD","target":"record","payload":{"canonical_record":{"source":{"id":"1711.06363","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-17T00:58:53Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"f4f2c1f077cdbfa1c5f80ba3bef583723f776c205ba92c8a28b18116ab4ef7af","abstract_canon_sha256":"30017b68867a74e444e11522f06ca85402657066a49d0b91ab151ef3db17d439"},"schema_version":"1.0"},"canonical_sha256":"c7d0b24b68052c08ae80af9b929a2198c858d2cadd611d29738caa9bbd44347f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:21:34.515752Z","signature_b64":"NdrVyiY7Ebpb+9eO/m661+zn+++90aYTG54BPKMc3NEVygMQp6wJua+qafubsYiEFr8bD8jdCDenjmfPmLa9DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c7d0b24b68052c08ae80af9b929a2198c858d2cadd611d29738caa9bbd44347f","last_reissued_at":"2026-05-18T00:21:34.515163Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:21:34.515163Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1711.06363","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":"2026-05-18T00:21:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fsei9lL7XEQn8/9p0ek1CTcJa2o2hch8ChRlKp+d0zb74QZ1OTVLBi0gQ3mEHNlxH4dKOS4gN3+U4OQVp0w+CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T20:08:43.485111Z"},"content_sha256":"df362cab9fe493f7752ab9f1a7ef30c37d2090de3596aa23792931ecb963a898","schema_version":"1.0","event_id":"sha256:df362cab9fe493f7752ab9f1a7ef30c37d2090de3596aa23792931ecb963a898"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:Y7ILES3IAUWARLUAV6NZFGRBTD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"3D Reconstruction of Incomplete Archaeological Objects Using a Generative Adversarial Network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Ivan Sipiran, Renato Hermoza","submitted_at":"2017-11-17T00:58:53Z","abstract_excerpt":"We introduce a data-driven approach to aid the repairing and conservation of archaeological objects: ORGAN, an object reconstruction generative adversarial network (GAN). By using an encoder-decoder 3D deep neural network on a GAN architecture, and combining two loss objectives: a completion loss and an Improved Wasserstein GAN loss, we can train a network to effectively predict the missing geometry of damaged objects. As archaeological objects can greatly differ between them, the network is conditioned on a variable, which can be a culture, a region or any metadata of the object. In our resul"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.06363","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":""},"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":"2026-05-18T00:21:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+PJZEe7jKs0hcWxJI6qWRW1X5a4QXdV8lli9QoKl3qwaeJR4dXSs/wcfduTwRo0nY+WKluf0mjPU7Jda1ucdDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T20:08:43.485594Z"},"content_sha256":"2f75a297e81e608f0468f2ddd6a69bfac9570bf61c8ac732d03cb727bcb83f28","schema_version":"1.0","event_id":"sha256:2f75a297e81e608f0468f2ddd6a69bfac9570bf61c8ac732d03cb727bcb83f28"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Y7ILES3IAUWARLUAV6NZFGRBTD/bundle.json","state_url":"https://pith.science/pith/Y7ILES3IAUWARLUAV6NZFGRBTD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Y7ILES3IAUWARLUAV6NZFGRBTD/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":"2026-08-07T20:08:43Z","links":{"resolver":"https://pith.science/pith/Y7ILES3IAUWARLUAV6NZFGRBTD","bundle":"https://pith.science/pith/Y7ILES3IAUWARLUAV6NZFGRBTD/bundle.json","state":"https://pith.science/pith/Y7ILES3IAUWARLUAV6NZFGRBTD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Y7ILES3IAUWARLUAV6NZFGRBTD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:Y7ILES3IAUWARLUAV6NZFGRBTD","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":"30017b68867a74e444e11522f06ca85402657066a49d0b91ab151ef3db17d439","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-17T00:58:53Z","title_canon_sha256":"f4f2c1f077cdbfa1c5f80ba3bef583723f776c205ba92c8a28b18116ab4ef7af"},"schema_version":"1.0","source":{"id":"1711.06363","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.06363","created_at":"2026-05-18T00:21:34Z"},{"alias_kind":"arxiv_version","alias_value":"1711.06363v2","created_at":"2026-05-18T00:21:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.06363","created_at":"2026-05-18T00:21:34Z"},{"alias_kind":"pith_short_12","alias_value":"Y7ILES3IAUWA","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_16","alias_value":"Y7ILES3IAUWARLUA","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_8","alias_value":"Y7ILES3I","created_at":"2026-05-18T12:31:56Z"}],"graph_snapshots":[{"event_id":"sha256:2f75a297e81e608f0468f2ddd6a69bfac9570bf61c8ac732d03cb727bcb83f28","target":"graph","created_at":"2026-05-18T00:21:34Z","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 a data-driven approach to aid the repairing and conservation of archaeological objects: ORGAN, an object reconstruction generative adversarial network (GAN). By using an encoder-decoder 3D deep neural network on a GAN architecture, and combining two loss objectives: a completion loss and an Improved Wasserstein GAN loss, we can train a network to effectively predict the missing geometry of damaged objects. As archaeological objects can greatly differ between them, the network is conditioned on a variable, which can be a culture, a region or any metadata of the object. In our resul","authors_text":"Ivan Sipiran, Renato Hermoza","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-17T00:58:53Z","title":"3D Reconstruction of Incomplete Archaeological Objects Using a Generative Adversarial Network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.06363","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:df362cab9fe493f7752ab9f1a7ef30c37d2090de3596aa23792931ecb963a898","target":"record","created_at":"2026-05-18T00:21:34Z","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":"30017b68867a74e444e11522f06ca85402657066a49d0b91ab151ef3db17d439","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-17T00:58:53Z","title_canon_sha256":"f4f2c1f077cdbfa1c5f80ba3bef583723f776c205ba92c8a28b18116ab4ef7af"},"schema_version":"1.0","source":{"id":"1711.06363","kind":"arxiv","version":2}},"canonical_sha256":"c7d0b24b68052c08ae80af9b929a2198c858d2cadd611d29738caa9bbd44347f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c7d0b24b68052c08ae80af9b929a2198c858d2cadd611d29738caa9bbd44347f","first_computed_at":"2026-05-18T00:21:34.515163Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:21:34.515163Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"NdrVyiY7Ebpb+9eO/m661+zn+++90aYTG54BPKMc3NEVygMQp6wJua+qafubsYiEFr8bD8jdCDenjmfPmLa9DA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:21:34.515752Z","signed_message":"canonical_sha256_bytes"},"source_id":"1711.06363","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:df362cab9fe493f7752ab9f1a7ef30c37d2090de3596aa23792931ecb963a898","sha256:2f75a297e81e608f0468f2ddd6a69bfac9570bf61c8ac732d03cb727bcb83f28"],"state_sha256":"f1977f000b115d7ee17f1e304e15c36171dfc033c157f7c4d9f3f7ff7300e8ed"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6wxXI5ysxUHjbFBYRwMuL+P20s+ppUK+/tbYLpXEFfJEBeUQ9RoBj3405n5zPq2ZptLFNTWc+lQaJn3UmutIBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T20:08:43.490580Z","bundle_sha256":"ac361ac1eef1c5bbc9c72658bebd90174d58a85f11e2130cbd08fd4b288f7c31"}}