{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:XREF5HVPOSX3QQ662UQYYHBALG","short_pith_number":"pith:XREF5HVP","schema_version":"1.0","canonical_sha256":"bc485e9eaf74afb843ded5218c1c20598a41e661c93f53a70b6ab20c4515bbe5","source":{"kind":"arxiv","id":"2104.10325","version":1},"attestation_state":"computed","paper":{"title":"SRWarp: Generalized Image Super-Resolution under Arbitrary Transformation","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Kyoung Mu Lee, Sanghyun Son","submitted_at":"2021-04-21T02:50:41Z","abstract_excerpt":"Deep CNNs have achieved significant successes in image processing and its applications, including single image super-resolution (SR). However, conventional methods still resort to some predetermined integer scaling factors, e.g., x2 or x4. Thus, they are difficult to be applied when arbitrary target resolutions are required. Recent approaches extend the scope to real-valued upsampling factors, even with varying aspect ratios to handle the limitation. In this paper, we propose the SRWarp framework to further generalize the SR tasks toward an arbitrary image transformation. We interpret the trad"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2104.10325","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2021-04-21T02:50:41Z","cross_cats_sorted":[],"title_canon_sha256":"42021aece7bdbc2afefb59782512ffb29b2c9539e44074a25b119aae3a6b0add","abstract_canon_sha256":"329fddd5b3e824e01d90eb104a043fe3b0a36df8d5e3fd945fa04a3c84f31aaf"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:34:01.201125Z","signature_b64":"tQBOw9o5LOO2vlOh0FyZVBd0T0nSPEM15gd4Mo1gOJbuIbFNWrvoqyXdLHtc3VT/2VIV+RV4lPoOyMozUBYTCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bc485e9eaf74afb843ded5218c1c20598a41e661c93f53a70b6ab20c4515bbe5","last_reissued_at":"2026-07-05T02:34:01.200782Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:34:01.200782Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"SRWarp: Generalized Image Super-Resolution under Arbitrary Transformation","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Kyoung Mu Lee, Sanghyun Son","submitted_at":"2021-04-21T02:50:41Z","abstract_excerpt":"Deep CNNs have achieved significant successes in image processing and its applications, including single image super-resolution (SR). However, conventional methods still resort to some predetermined integer scaling factors, e.g., x2 or x4. Thus, they are difficult to be applied when arbitrary target resolutions are required. Recent approaches extend the scope to real-valued upsampling factors, even with varying aspect ratios to handle the limitation. In this paper, we propose the SRWarp framework to further generalize the SR tasks toward an arbitrary image transformation. We interpret the trad"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.10325","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2104.10325/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2104.10325","created_at":"2026-07-05T02:34:01.200832+00:00"},{"alias_kind":"arxiv_version","alias_value":"2104.10325v1","created_at":"2026-07-05T02:34:01.200832+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.10325","created_at":"2026-07-05T02:34:01.200832+00:00"},{"alias_kind":"pith_short_12","alias_value":"XREF5HVPOSX3","created_at":"2026-07-05T02:34:01.200832+00:00"},{"alias_kind":"pith_short_16","alias_value":"XREF5HVPOSX3QQ66","created_at":"2026-07-05T02:34:01.200832+00:00"},{"alias_kind":"pith_short_8","alias_value":"XREF5HVP","created_at":"2026-07-05T02:34:01.200832+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/XREF5HVPOSX3QQ662UQYYHBALG","json":"https://pith.science/pith/XREF5HVPOSX3QQ662UQYYHBALG.json","graph_json":"https://pith.science/api/pith-number/XREF5HVPOSX3QQ662UQYYHBALG/graph.json","events_json":"https://pith.science/api/pith-number/XREF5HVPOSX3QQ662UQYYHBALG/events.json","paper":"https://pith.science/paper/XREF5HVP"},"agent_actions":{"view_html":"https://pith.science/pith/XREF5HVPOSX3QQ662UQYYHBALG","download_json":"https://pith.science/pith/XREF5HVPOSX3QQ662UQYYHBALG.json","view_paper":"https://pith.science/paper/XREF5HVP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2104.10325&json=true","fetch_graph":"https://pith.science/api/pith-number/XREF5HVPOSX3QQ662UQYYHBALG/graph.json","fetch_events":"https://pith.science/api/pith-number/XREF5HVPOSX3QQ662UQYYHBALG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XREF5HVPOSX3QQ662UQYYHBALG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XREF5HVPOSX3QQ662UQYYHBALG/action/storage_attestation","attest_author":"https://pith.science/pith/XREF5HVPOSX3QQ662UQYYHBALG/action/author_attestation","sign_citation":"https://pith.science/pith/XREF5HVPOSX3QQ662UQYYHBALG/action/citation_signature","submit_replication":"https://pith.science/pith/XREF5HVPOSX3QQ662UQYYHBALG/action/replication_record"}},"created_at":"2026-07-05T02:34:01.200832+00:00","updated_at":"2026-07-05T02:34:01.200832+00:00"}