{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:J7EB6MFCFOGSWR5EPZJMIPVCLK","short_pith_number":"pith:J7EB6MFC","canonical_record":{"source":{"id":"2109.14335","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2021-09-29T10:41:41Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"5b9f8928170676e5335dec5c7902e21f0cabb8620f046412440f60afc7e7149b","abstract_canon_sha256":"9520ce12d06002d71eb46ce7c8ab1609aab5aad4ea5d8f7cdce46fbf983c2ee5"},"schema_version":"1.0"},"canonical_sha256":"4fc81f30a22b8d2b47a47e52c43ea25a85ed9d4732c6defd1761245fd2f9f7c7","source":{"kind":"arxiv","id":"2109.14335","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2109.14335","created_at":"2026-07-05T08:07:07Z"},{"alias_kind":"arxiv_version","alias_value":"2109.14335v2","created_at":"2026-07-05T08:07:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.14335","created_at":"2026-07-05T08:07:07Z"},{"alias_kind":"pith_short_12","alias_value":"J7EB6MFCFOGS","created_at":"2026-07-05T08:07:07Z"},{"alias_kind":"pith_short_16","alias_value":"J7EB6MFCFOGSWR5E","created_at":"2026-07-05T08:07:07Z"},{"alias_kind":"pith_short_8","alias_value":"J7EB6MFC","created_at":"2026-07-05T08:07:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:J7EB6MFCFOGSWR5EPZJMIPVCLK","target":"record","payload":{"canonical_record":{"source":{"id":"2109.14335","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2021-09-29T10:41:41Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"5b9f8928170676e5335dec5c7902e21f0cabb8620f046412440f60afc7e7149b","abstract_canon_sha256":"9520ce12d06002d71eb46ce7c8ab1609aab5aad4ea5d8f7cdce46fbf983c2ee5"},"schema_version":"1.0"},"canonical_sha256":"4fc81f30a22b8d2b47a47e52c43ea25a85ed9d4732c6defd1761245fd2f9f7c7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:07:07.236375Z","signature_b64":"uXwK0NGrdtx1HUFdOs2Wgv9NtU2buFbMo/um6DulfvgVPoWZo0SS+ADrqpfynMJdkcIdA4tWkcjH6bpOYFB9Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4fc81f30a22b8d2b47a47e52c43ea25a85ed9d4732c6defd1761245fd2f9f7c7","last_reissued_at":"2026-07-05T08:07:07.235943Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:07:07.235943Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2109.14335","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":"2026-07-05T08:07:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pNN7PzwMi0c5f+G41cTzexO7PYhnqBCx71ysub904phW6E4BkWO2Y0gCAiNB9Vr9lbfAL1DkMhYNlws63SqMAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T12:31:11.498831Z"},"content_sha256":"003e2a1e32a323dedf3fe770ceabb79ae0665dbad7019d03d367a7e5a29ceff4","schema_version":"1.0","event_id":"sha256:003e2a1e32a323dedf3fe770ceabb79ae0665dbad7019d03d367a7e5a29ceff4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:J7EB6MFCFOGSWR5EPZJMIPVCLK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Systematic Survey of Deep Learning-based Single-Image Super-Resolution","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"eess.IV","authors_text":"Guangwei Gao, Juncheng Li, Longguang Wang, Tieyong Zeng, Wenjie Li, Yingqian Wang, Zehua Pei","submitted_at":"2021-09-29T10:41:41Z","abstract_excerpt":"Single-image super-resolution (SISR) is an important task in image processing, which aims to enhance the resolution of imaging systems. Recently, SISR has made a huge leap and has achieved promising results with the help of deep learning (DL). In this survey, we give an overview of DL-based SISR methods and group them according to their design targets. Specifically, we first introduce the problem definition, research background, and the significance of SISR. Secondly, we introduce some related works, including benchmark datasets, upsampling methods, optimization objectives, and image quality a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.14335","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2109.14335/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T08:07:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QpTvNFKPEsIlms06hTjP+qNiQwVyUYndAJJ7XWZ5Sd5TSHixZuC2hGaqMoOs9dnZ8120EzooT9mKYAa3/YAKBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T12:31:11.499353Z"},"content_sha256":"593cfebfdd10b0eeadfc7c72ed3e91cfe309e844ca6f35b4e62ac2e9718f5a8c","schema_version":"1.0","event_id":"sha256:593cfebfdd10b0eeadfc7c72ed3e91cfe309e844ca6f35b4e62ac2e9718f5a8c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/J7EB6MFCFOGSWR5EPZJMIPVCLK/bundle.json","state_url":"https://pith.science/pith/J7EB6MFCFOGSWR5EPZJMIPVCLK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/J7EB6MFCFOGSWR5EPZJMIPVCLK/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":"2026-08-07T12:31:11Z","links":{"resolver":"https://pith.science/pith/J7EB6MFCFOGSWR5EPZJMIPVCLK","bundle":"https://pith.science/pith/J7EB6MFCFOGSWR5EPZJMIPVCLK/bundle.json","state":"https://pith.science/pith/J7EB6MFCFOGSWR5EPZJMIPVCLK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/J7EB6MFCFOGSWR5EPZJMIPVCLK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:J7EB6MFCFOGSWR5EPZJMIPVCLK","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":"9520ce12d06002d71eb46ce7c8ab1609aab5aad4ea5d8f7cdce46fbf983c2ee5","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2021-09-29T10:41:41Z","title_canon_sha256":"5b9f8928170676e5335dec5c7902e21f0cabb8620f046412440f60afc7e7149b"},"schema_version":"1.0","source":{"id":"2109.14335","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2109.14335","created_at":"2026-07-05T08:07:07Z"},{"alias_kind":"arxiv_version","alias_value":"2109.14335v2","created_at":"2026-07-05T08:07:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.14335","created_at":"2026-07-05T08:07:07Z"},{"alias_kind":"pith_short_12","alias_value":"J7EB6MFCFOGS","created_at":"2026-07-05T08:07:07Z"},{"alias_kind":"pith_short_16","alias_value":"J7EB6MFCFOGSWR5E","created_at":"2026-07-05T08:07:07Z"},{"alias_kind":"pith_short_8","alias_value":"J7EB6MFC","created_at":"2026-07-05T08:07:07Z"}],"graph_snapshots":[{"event_id":"sha256:593cfebfdd10b0eeadfc7c72ed3e91cfe309e844ca6f35b4e62ac2e9718f5a8c","target":"graph","created_at":"2026-07-05T08:07:07Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2109.14335/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Single-image super-resolution (SISR) is an important task in image processing, which aims to enhance the resolution of imaging systems. Recently, SISR has made a huge leap and has achieved promising results with the help of deep learning (DL). In this survey, we give an overview of DL-based SISR methods and group them according to their design targets. Specifically, we first introduce the problem definition, research background, and the significance of SISR. Secondly, we introduce some related works, including benchmark datasets, upsampling methods, optimization objectives, and image quality a","authors_text":"Guangwei Gao, Juncheng Li, Longguang Wang, Tieyong Zeng, Wenjie Li, Yingqian Wang, Zehua Pei","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2021-09-29T10:41:41Z","title":"A Systematic Survey of Deep Learning-based Single-Image Super-Resolution"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.14335","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":"sha256:003e2a1e32a323dedf3fe770ceabb79ae0665dbad7019d03d367a7e5a29ceff4","target":"record","created_at":"2026-07-05T08:07:07Z","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":"9520ce12d06002d71eb46ce7c8ab1609aab5aad4ea5d8f7cdce46fbf983c2ee5","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2021-09-29T10:41:41Z","title_canon_sha256":"5b9f8928170676e5335dec5c7902e21f0cabb8620f046412440f60afc7e7149b"},"schema_version":"1.0","source":{"id":"2109.14335","kind":"arxiv","version":2}},"canonical_sha256":"4fc81f30a22b8d2b47a47e52c43ea25a85ed9d4732c6defd1761245fd2f9f7c7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4fc81f30a22b8d2b47a47e52c43ea25a85ed9d4732c6defd1761245fd2f9f7c7","first_computed_at":"2026-07-05T08:07:07.235943Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:07:07.235943Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"uXwK0NGrdtx1HUFdOs2Wgv9NtU2buFbMo/um6DulfvgVPoWZo0SS+ADrqpfynMJdkcIdA4tWkcjH6bpOYFB9Cg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:07:07.236375Z","signed_message":"canonical_sha256_bytes"},"source_id":"2109.14335","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:003e2a1e32a323dedf3fe770ceabb79ae0665dbad7019d03d367a7e5a29ceff4","sha256:593cfebfdd10b0eeadfc7c72ed3e91cfe309e844ca6f35b4e62ac2e9718f5a8c"],"state_sha256":"00a74c071a76ab7e4f101279d2884f25ba331c0daa7db322b20eeb3ee81a0504"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"X87cuBcvMQLYE0NjhOULinzw54/UtWWYlD5JmJxdrJ45O2kcqTANgPS9TxEoXynozeuC7cynn2foy3k7V4SOAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T12:31:11.510659Z","bundle_sha256":"bdfa944d06d1ec697d053db0a5ad2bf330d8d4027e68c48353c85bd7fbaf9a67"}}