{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:K7XWAKXKJQK2GJKOYO5RJDTDKZ","short_pith_number":"pith:K7XWAKXK","canonical_record":{"source":{"id":"1812.11834","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-19T11:53:40Z","cross_cats_sorted":[],"title_canon_sha256":"67c6a1f9d827df97de1f8694aa6289c84f95d1f89b0e3f4b39d0dc8bbe058e31","abstract_canon_sha256":"f8d38ae966fec13a249dcab173ebedeaa3b61c85113aca18e3d84603e123047e"},"schema_version":"1.0"},"canonical_sha256":"57ef602aea4c15a3254ec3bb148e6356698f3cfb6d718bff9bab8482f659b22a","source":{"kind":"arxiv","id":"1812.11834","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.11834","created_at":"2026-05-17T23:57:11Z"},{"alias_kind":"arxiv_version","alias_value":"1812.11834v1","created_at":"2026-05-17T23:57:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.11834","created_at":"2026-05-17T23:57:11Z"},{"alias_kind":"pith_short_12","alias_value":"K7XWAKXKJQK2","created_at":"2026-05-18T12:32:33Z"},{"alias_kind":"pith_short_16","alias_value":"K7XWAKXKJQK2GJKO","created_at":"2026-05-18T12:32:33Z"},{"alias_kind":"pith_short_8","alias_value":"K7XWAKXK","created_at":"2026-05-18T12:32:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:K7XWAKXKJQK2GJKOYO5RJDTDKZ","target":"record","payload":{"canonical_record":{"source":{"id":"1812.11834","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-19T11:53:40Z","cross_cats_sorted":[],"title_canon_sha256":"67c6a1f9d827df97de1f8694aa6289c84f95d1f89b0e3f4b39d0dc8bbe058e31","abstract_canon_sha256":"f8d38ae966fec13a249dcab173ebedeaa3b61c85113aca18e3d84603e123047e"},"schema_version":"1.0"},"canonical_sha256":"57ef602aea4c15a3254ec3bb148e6356698f3cfb6d718bff9bab8482f659b22a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:57:11.028940Z","signature_b64":"6kHJFuPcE8DO7e2ta3rWEdcHXGTYjHwfsxMbeGNXEVtvr25G6bDmeOuH9o3qSKFm+WTbwqW+1kiSRETHyDWdDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"57ef602aea4c15a3254ec3bb148e6356698f3cfb6d718bff9bab8482f659b22a","last_reissued_at":"2026-05-17T23:57:11.028413Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:57:11.028413Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1812.11834","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":"2026-05-17T23:57:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ou7NOOUmyquEdWTzdfxDi37rhyljdGUp5JRfvu7IUmnT5O2b5EOgJTaM0Ga1b4W1PHlrR0vtyOV8Y9fOp7jLCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T01:48:29.662112Z"},"content_sha256":"7c4a80bac6f6a69c9527a1947a53b9dcbdca7e996649e07d717effaec8bfbc7b","schema_version":"1.0","event_id":"sha256:7c4a80bac6f6a69c9527a1947a53b9dcbdca7e996649e07d717effaec8bfbc7b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:K7XWAKXKJQK2GJKOYO5RJDTDKZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Sequential Gating Ensemble Network for Noise Robust Multi-Scale Face Restoration","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Feng Wu, Jianxin Lin, Tiankuang Zhou, Zhibo Chen","submitted_at":"2018-12-19T11:53:40Z","abstract_excerpt":"Face restoration from low resolution and noise is important for applications of face analysis recognition. However, most existing face restoration models omit the multiple scale issues in face restoration problem, which is still not well-solved in research area. In this paper, we propose a Sequential Gating Ensemble Network (SGEN) for multi-scale noise robust face restoration issue. To endow the network with multi-scale representation ability, we first employ the principle of ensemble learning for SGEN network architecture designing. The SGEN aggregates multi-level base-encoders and base-decod"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.11834","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":"2026-05-17T23:57:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MsnMsPoEtxLH0YdxO5BPl79WRmUkHwIF0nTZ3pIPPL53KadKZVXLBlNr4d7isVVgXBhZzgglTdCZ2ilJOkWLCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T01:48:29.662771Z"},"content_sha256":"662c7fc18065e0a8e0c5c13b8afac9d2365d7055a5be91037680fe60bc2305af","schema_version":"1.0","event_id":"sha256:662c7fc18065e0a8e0c5c13b8afac9d2365d7055a5be91037680fe60bc2305af"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/K7XWAKXKJQK2GJKOYO5RJDTDKZ/bundle.json","state_url":"https://pith.science/pith/K7XWAKXKJQK2GJKOYO5RJDTDKZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/K7XWAKXKJQK2GJKOYO5RJDTDKZ/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":"2026-05-27T01:48:29Z","links":{"resolver":"https://pith.science/pith/K7XWAKXKJQK2GJKOYO5RJDTDKZ","bundle":"https://pith.science/pith/K7XWAKXKJQK2GJKOYO5RJDTDKZ/bundle.json","state":"https://pith.science/pith/K7XWAKXKJQK2GJKOYO5RJDTDKZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/K7XWAKXKJQK2GJKOYO5RJDTDKZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:K7XWAKXKJQK2GJKOYO5RJDTDKZ","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":"f8d38ae966fec13a249dcab173ebedeaa3b61c85113aca18e3d84603e123047e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-19T11:53:40Z","title_canon_sha256":"67c6a1f9d827df97de1f8694aa6289c84f95d1f89b0e3f4b39d0dc8bbe058e31"},"schema_version":"1.0","source":{"id":"1812.11834","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.11834","created_at":"2026-05-17T23:57:11Z"},{"alias_kind":"arxiv_version","alias_value":"1812.11834v1","created_at":"2026-05-17T23:57:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.11834","created_at":"2026-05-17T23:57:11Z"},{"alias_kind":"pith_short_12","alias_value":"K7XWAKXKJQK2","created_at":"2026-05-18T12:32:33Z"},{"alias_kind":"pith_short_16","alias_value":"K7XWAKXKJQK2GJKO","created_at":"2026-05-18T12:32:33Z"},{"alias_kind":"pith_short_8","alias_value":"K7XWAKXK","created_at":"2026-05-18T12:32:33Z"}],"graph_snapshots":[{"event_id":"sha256:662c7fc18065e0a8e0c5c13b8afac9d2365d7055a5be91037680fe60bc2305af","target":"graph","created_at":"2026-05-17T23:57:11Z","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 restoration from low resolution and noise is important for applications of face analysis recognition. However, most existing face restoration models omit the multiple scale issues in face restoration problem, which is still not well-solved in research area. In this paper, we propose a Sequential Gating Ensemble Network (SGEN) for multi-scale noise robust face restoration issue. To endow the network with multi-scale representation ability, we first employ the principle of ensemble learning for SGEN network architecture designing. The SGEN aggregates multi-level base-encoders and base-decod","authors_text":"Feng Wu, Jianxin Lin, Tiankuang Zhou, Zhibo Chen","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-19T11:53:40Z","title":"Sequential Gating Ensemble Network for Noise Robust Multi-Scale Face Restoration"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.11834","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":"sha256:7c4a80bac6f6a69c9527a1947a53b9dcbdca7e996649e07d717effaec8bfbc7b","target":"record","created_at":"2026-05-17T23:57:11Z","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":"f8d38ae966fec13a249dcab173ebedeaa3b61c85113aca18e3d84603e123047e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-19T11:53:40Z","title_canon_sha256":"67c6a1f9d827df97de1f8694aa6289c84f95d1f89b0e3f4b39d0dc8bbe058e31"},"schema_version":"1.0","source":{"id":"1812.11834","kind":"arxiv","version":1}},"canonical_sha256":"57ef602aea4c15a3254ec3bb148e6356698f3cfb6d718bff9bab8482f659b22a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"57ef602aea4c15a3254ec3bb148e6356698f3cfb6d718bff9bab8482f659b22a","first_computed_at":"2026-05-17T23:57:11.028413Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:57:11.028413Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6kHJFuPcE8DO7e2ta3rWEdcHXGTYjHwfsxMbeGNXEVtvr25G6bDmeOuH9o3qSKFm+WTbwqW+1kiSRETHyDWdDQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:57:11.028940Z","signed_message":"canonical_sha256_bytes"},"source_id":"1812.11834","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7c4a80bac6f6a69c9527a1947a53b9dcbdca7e996649e07d717effaec8bfbc7b","sha256:662c7fc18065e0a8e0c5c13b8afac9d2365d7055a5be91037680fe60bc2305af"],"state_sha256":"33aed185033cc2fbc76c5c2705db9da751eae2ae9286f79efc7f0f3f95ad4f25"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/dGbaB4ltkMhEBP/Tu23IOaAYPuxQxHbJIQmfB7CnbWPzR4LUgO5ntbMZOiTdJ9+cQ6h3PfakaJwQS0qbF1BAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T01:48:29.665722Z","bundle_sha256":"fc88df0e55cb0624775bbdcf1eb62f0741f4dfd740181f5a9081006c9871aead"}}