{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:F37YT3YEK5JEOLVO7MTPSLWDLZ","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":"864783cb00b4928f2260117a025e64a1c830f29c691f07be5fe867ac4dcbbeac","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-19T09:39:41Z","title_canon_sha256":"887e6f98410e78a87df1b50ddb114c861d1fb8aeedc47f9e3366885ce4412708"},"schema_version":"1.0","source":{"id":"1809.07099","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.07099","created_at":"2026-05-18T00:05:20Z"},{"alias_kind":"arxiv_version","alias_value":"1809.07099v1","created_at":"2026-05-18T00:05:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.07099","created_at":"2026-05-18T00:05:20Z"},{"alias_kind":"pith_short_12","alias_value":"F37YT3YEK5JE","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_16","alias_value":"F37YT3YEK5JEOLVO","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_8","alias_value":"F37YT3YE","created_at":"2026-05-18T12:32:22Z"}],"graph_snapshots":[{"event_id":"sha256:f6d7d862c0cbb154ced8f356961e85a2e2a9349ee079f0538d769be051862770","target":"graph","created_at":"2026-05-18T00:05:20Z","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":"Deep neural networks have exhibited promising performance in image super-resolution (SR) due to the power in learning the non-linear mapping from low-resolution (LR) images to high-resolution (HR) images. However, most deep learning methods employ feed-forward architectures, and thus the dependencies between LR and HR images are not fully exploited, leading to limited learning performance. Moreover, most deep learning based SR methods apply the pixel-wise reconstruction error as the loss, which, however, may fail to capture high-frequency information and produce perceptually unsatisfying resul","authors_text":"Jian Chen, Jiezhang Cao, Junzhou Huang, Mingkui Tan, Peilin Zhao, Qi Chen, Yanwu Xu, Yong Guo","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-19T09:39:41Z","title":"Dual Reconstruction Nets for Image Super-Resolution with Gradient Sensitive Loss"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.07099","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":"sha256:82371a07ec610ea1b2a145aea6ba58f53748af586d0b5747f1f61c87cb67d5e5","target":"record","created_at":"2026-05-18T00:05:20Z","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":"864783cb00b4928f2260117a025e64a1c830f29c691f07be5fe867ac4dcbbeac","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-19T09:39:41Z","title_canon_sha256":"887e6f98410e78a87df1b50ddb114c861d1fb8aeedc47f9e3366885ce4412708"},"schema_version":"1.0","source":{"id":"1809.07099","kind":"arxiv","version":1}},"canonical_sha256":"2eff89ef045752472eaefb26f92ec35e5d008dd74bc3bff8d32f60495cc61d08","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2eff89ef045752472eaefb26f92ec35e5d008dd74bc3bff8d32f60495cc61d08","first_computed_at":"2026-05-18T00:05:20.671942Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:05:20.671942Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"JaIilg+StMjNMiFLHByxBDe2d/Zd+oaVCdqpIAa0sfKB6AYjjzo5pRIMhs4LdfZqZB9TVdP523ZOcZUgmAA2Aw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:05:20.672703Z","signed_message":"canonical_sha256_bytes"},"source_id":"1809.07099","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:82371a07ec610ea1b2a145aea6ba58f53748af586d0b5747f1f61c87cb67d5e5","sha256:f6d7d862c0cbb154ced8f356961e85a2e2a9349ee079f0538d769be051862770"],"state_sha256":"52022ecb0b43e975fa43e0e65fd54a1972f97c14de7d8f701484a88dd66f6b61"}