{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:7IKRGR4ZKWBOSIINDA3ZGFL4C2","short_pith_number":"pith:7IKRGR4Z","canonical_record":{"source":{"id":"1809.00665","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-03T17:23:38Z","cross_cats_sorted":[],"title_canon_sha256":"57a97d7419eb9a8202ee0eb2ac1632a5e9e4b11041f962e003d49545d71cb524","abstract_canon_sha256":"0337ee37240fac0fb20cd9fb301e21a1392b645184d3c4b7a6bfdc51be3250a9"},"schema_version":"1.0"},"canonical_sha256":"fa151347995582e9210d183793157c16aff7ae2ff3668e04a9e2d1c7fd8388b0","source":{"kind":"arxiv","id":"1809.00665","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.00665","created_at":"2026-05-18T00:05:40Z"},{"alias_kind":"arxiv_version","alias_value":"1809.00665v2","created_at":"2026-05-18T00:05:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.00665","created_at":"2026-05-18T00:05:40Z"},{"alias_kind":"pith_short_12","alias_value":"7IKRGR4ZKWBO","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_16","alias_value":"7IKRGR4ZKWBOSIIN","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_8","alias_value":"7IKRGR4Z","created_at":"2026-05-18T12:32:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:7IKRGR4ZKWBOSIINDA3ZGFL4C2","target":"record","payload":{"canonical_record":{"source":{"id":"1809.00665","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-03T17:23:38Z","cross_cats_sorted":[],"title_canon_sha256":"57a97d7419eb9a8202ee0eb2ac1632a5e9e4b11041f962e003d49545d71cb524","abstract_canon_sha256":"0337ee37240fac0fb20cd9fb301e21a1392b645184d3c4b7a6bfdc51be3250a9"},"schema_version":"1.0"},"canonical_sha256":"fa151347995582e9210d183793157c16aff7ae2ff3668e04a9e2d1c7fd8388b0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:05:40.791370Z","signature_b64":"1tf9VQiUj+V/UPQ4EAnsPX4NOROfpGDd7wpqRhLOHibR51PlEZ2aK2dyp50IIAZX35MULfYVyKU6lEsidncuAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fa151347995582e9210d183793157c16aff7ae2ff3668e04a9e2d1c7fd8388b0","last_reissued_at":"2026-05-18T00:05:40.790658Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:05:40.790658Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1809.00665","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":"2026-05-18T00:05:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1V5DsrHJ0E+JucV1i4ovg+xPfl/kCjj4SY9ulVrJS9xjv/wBCa8TWYV627FGmouO5bOQMN/MWc84GNFYbzyNBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T07:28:52.333054Z"},"content_sha256":"5d4fce122fc748944619cdbed0916e8483b859929a5929d0436b0ac83990e531","schema_version":"1.0","event_id":"sha256:5d4fce122fc748944619cdbed0916e8483b859929a5929d0436b0ac83990e531"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:7IKRGR4ZKWBOSIINDA3ZGFL4C2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Context-Patch Face Hallucination Based on Thresholding Locality-constrained Representation and Reproducing Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Akiko Aizawa, Jiayi Ma, Junjun Jiang, Kiyoharu Aizawa, Suhua Tang, Yi Yu","submitted_at":"2018-09-03T17:23:38Z","abstract_excerpt":"Face hallucination is a technique that reconstruct high-resolution (HR) faces from low-resolution (LR) faces, by using the prior knowledge learned from HR/LR face pairs. Most state-of-the-arts leverage position-patch prior knowledge of human face to estimate the optimal representation coefficients for each image patch. However, they focus only the position information and usually ignore the context information of image patch. In addition, when they are confronted with misalignment or the Small Sample Size (SSS) problem, the hallucination performance is very poor. To this end, this study incorp"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.00665","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":"2026-05-18T00:05:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MGRu9YMjkJkulsV2srVamL/DPPUKpzolBGENZ0zS6M99oifE9UU4zBawVd7yaZc+upYV6rABZasA49Zuvu5GBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T07:28:52.333821Z"},"content_sha256":"b259856b783933aafeb1485e96cd749cf8473c009911252dbe7535b575973a5e","schema_version":"1.0","event_id":"sha256:b259856b783933aafeb1485e96cd749cf8473c009911252dbe7535b575973a5e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7IKRGR4ZKWBOSIINDA3ZGFL4C2/bundle.json","state_url":"https://pith.science/pith/7IKRGR4ZKWBOSIINDA3ZGFL4C2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7IKRGR4ZKWBOSIINDA3ZGFL4C2/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":"2026-05-26T07:28:52Z","links":{"resolver":"https://pith.science/pith/7IKRGR4ZKWBOSIINDA3ZGFL4C2","bundle":"https://pith.science/pith/7IKRGR4ZKWBOSIINDA3ZGFL4C2/bundle.json","state":"https://pith.science/pith/7IKRGR4ZKWBOSIINDA3ZGFL4C2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7IKRGR4ZKWBOSIINDA3ZGFL4C2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:7IKRGR4ZKWBOSIINDA3ZGFL4C2","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":"0337ee37240fac0fb20cd9fb301e21a1392b645184d3c4b7a6bfdc51be3250a9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-03T17:23:38Z","title_canon_sha256":"57a97d7419eb9a8202ee0eb2ac1632a5e9e4b11041f962e003d49545d71cb524"},"schema_version":"1.0","source":{"id":"1809.00665","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.00665","created_at":"2026-05-18T00:05:40Z"},{"alias_kind":"arxiv_version","alias_value":"1809.00665v2","created_at":"2026-05-18T00:05:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.00665","created_at":"2026-05-18T00:05:40Z"},{"alias_kind":"pith_short_12","alias_value":"7IKRGR4ZKWBO","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_16","alias_value":"7IKRGR4ZKWBOSIIN","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_8","alias_value":"7IKRGR4Z","created_at":"2026-05-18T12:32:11Z"}],"graph_snapshots":[{"event_id":"sha256:b259856b783933aafeb1485e96cd749cf8473c009911252dbe7535b575973a5e","target":"graph","created_at":"2026-05-18T00:05:40Z","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":"Face hallucination is a technique that reconstruct high-resolution (HR) faces from low-resolution (LR) faces, by using the prior knowledge learned from HR/LR face pairs. Most state-of-the-arts leverage position-patch prior knowledge of human face to estimate the optimal representation coefficients for each image patch. However, they focus only the position information and usually ignore the context information of image patch. In addition, when they are confronted with misalignment or the Small Sample Size (SSS) problem, the hallucination performance is very poor. To this end, this study incorp","authors_text":"Akiko Aizawa, Jiayi Ma, Junjun Jiang, Kiyoharu Aizawa, Suhua Tang, Yi Yu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-03T17:23:38Z","title":"Context-Patch Face Hallucination Based on Thresholding Locality-constrained Representation and Reproducing Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.00665","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":"sha256:5d4fce122fc748944619cdbed0916e8483b859929a5929d0436b0ac83990e531","target":"record","created_at":"2026-05-18T00:05:40Z","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":"0337ee37240fac0fb20cd9fb301e21a1392b645184d3c4b7a6bfdc51be3250a9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-03T17:23:38Z","title_canon_sha256":"57a97d7419eb9a8202ee0eb2ac1632a5e9e4b11041f962e003d49545d71cb524"},"schema_version":"1.0","source":{"id":"1809.00665","kind":"arxiv","version":2}},"canonical_sha256":"fa151347995582e9210d183793157c16aff7ae2ff3668e04a9e2d1c7fd8388b0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fa151347995582e9210d183793157c16aff7ae2ff3668e04a9e2d1c7fd8388b0","first_computed_at":"2026-05-18T00:05:40.790658Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:05:40.790658Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1tf9VQiUj+V/UPQ4EAnsPX4NOROfpGDd7wpqRhLOHibR51PlEZ2aK2dyp50IIAZX35MULfYVyKU6lEsidncuAg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:05:40.791370Z","signed_message":"canonical_sha256_bytes"},"source_id":"1809.00665","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5d4fce122fc748944619cdbed0916e8483b859929a5929d0436b0ac83990e531","sha256:b259856b783933aafeb1485e96cd749cf8473c009911252dbe7535b575973a5e"],"state_sha256":"94270838ad6548c8c1772ca266f11ea63f2fc0f65d776f1b7f8c3a67226fadec"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GqXGMpQg5usstU16kAEHRwgKDJ8ljVfMj9JWe143noA1qaxuujG5LY+zaWZd54qpPb8L/wpjo/EYX9+/GglFDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T07:28:52.337713Z","bundle_sha256":"bd9352f047fefd32c934bcaa0b2de3ea86bd2661b92273855eedfb6757352c99"}}