{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:L5K4MKKIREM7OL4A6BJIO7R5EV","short_pith_number":"pith:L5K4MKKI","schema_version":"1.0","canonical_sha256":"5f55c629488919f72f80f052877e3d254614800ffb88c72ae6482a45e35684ea","source":{"kind":"arxiv","id":"2603.02692","version":1},"attestation_state":"computed","paper":{"title":"FiDeSR: High-Fidelity and Detail-Preserving One-Step Diffusion Super-Resolution","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Aro Kim, Chaewon Moon, Jinwoo Jeong, Myeongjin Jang, Sang-hyo Park, Youngjin Shin","submitted_at":"2026-03-03T07:34:49Z","abstract_excerpt":"Diffusion-based approaches have recently driven remarkable progress in real-world image super-resolution (SR). However, existing methods still struggle to simultaneously preserve fine details and ensure high-fidelity reconstruction, often resulting in suboptimal visual quality. In this paper, we propose FiDeSR, a high-fidelity and detail-preserving one-step diffusion super-resolution framework. During training, we introduce a detail-aware weighting strategy that adaptively emphasizes regions where the model exhibits higher prediction errors. During inference, low- and high-frequency adaptive e"},"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":"2603.02692","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-03-03T07:34:49Z","cross_cats_sorted":[],"title_canon_sha256":"7d757b4257630b9b5049e968744afed3cf0ee34afb5b56eb2c998c2daa7f499c","abstract_canon_sha256":"ee722091a869201dd42b60e554e1791ee446786c7a94688155018a9b2da91018"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-28T02:23:27.285031Z","signature_b64":"hD2dGXwNON5jsVGrzqKMu9qjTPSEIk8FMYrmvZijTEOzI3P4e2pZwccJkTNCQzNmXMJvalz4nrSyvbKQMXPMCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5f55c629488919f72f80f052877e3d254614800ffb88c72ae6482a45e35684ea","last_reissued_at":"2026-07-28T02:23:27.283960Z","signature_status":"signed_v1","first_computed_at":"2026-07-28T02:23:27.283960Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"FiDeSR: High-Fidelity and Detail-Preserving One-Step Diffusion Super-Resolution","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Aro Kim, Chaewon Moon, Jinwoo Jeong, Myeongjin Jang, Sang-hyo Park, Youngjin Shin","submitted_at":"2026-03-03T07:34:49Z","abstract_excerpt":"Diffusion-based approaches have recently driven remarkable progress in real-world image super-resolution (SR). However, existing methods still struggle to simultaneously preserve fine details and ensure high-fidelity reconstruction, often resulting in suboptimal visual quality. In this paper, we propose FiDeSR, a high-fidelity and detail-preserving one-step diffusion super-resolution framework. During training, we introduce a detail-aware weighting strategy that adaptively emphasizes regions where the model exhibits higher prediction errors. During inference, low- and high-frequency adaptive e"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2603.02692","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/2603.02692/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":"2603.02692","created_at":"2026-07-28T02:23:27.284463+00:00"},{"alias_kind":"arxiv_version","alias_value":"2603.02692v1","created_at":"2026-07-28T02:23:27.284463+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2603.02692","created_at":"2026-07-28T02:23:27.284463+00:00"},{"alias_kind":"pith_short_12","alias_value":"L5K4MKKIREM7","created_at":"2026-07-28T02:23:27.284463+00:00"},{"alias_kind":"pith_short_16","alias_value":"L5K4MKKIREM7OL4A","created_at":"2026-07-28T02:23:27.284463+00:00"},{"alias_kind":"pith_short_8","alias_value":"L5K4MKKI","created_at":"2026-07-28T02:23:27.284463+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/L5K4MKKIREM7OL4A6BJIO7R5EV","json":"https://pith.science/pith/L5K4MKKIREM7OL4A6BJIO7R5EV.json","graph_json":"https://pith.science/api/pith-number/L5K4MKKIREM7OL4A6BJIO7R5EV/graph.json","events_json":"https://pith.science/api/pith-number/L5K4MKKIREM7OL4A6BJIO7R5EV/events.json","paper":"https://pith.science/paper/L5K4MKKI"},"agent_actions":{"view_html":"https://pith.science/pith/L5K4MKKIREM7OL4A6BJIO7R5EV","download_json":"https://pith.science/pith/L5K4MKKIREM7OL4A6BJIO7R5EV.json","view_paper":"https://pith.science/paper/L5K4MKKI","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2603.02692&json=true","fetch_graph":"https://pith.science/api/pith-number/L5K4MKKIREM7OL4A6BJIO7R5EV/graph.json","fetch_events":"https://pith.science/api/pith-number/L5K4MKKIREM7OL4A6BJIO7R5EV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/L5K4MKKIREM7OL4A6BJIO7R5EV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/L5K4MKKIREM7OL4A6BJIO7R5EV/action/storage_attestation","attest_author":"https://pith.science/pith/L5K4MKKIREM7OL4A6BJIO7R5EV/action/author_attestation","sign_citation":"https://pith.science/pith/L5K4MKKIREM7OL4A6BJIO7R5EV/action/citation_signature","submit_replication":"https://pith.science/pith/L5K4MKKIREM7OL4A6BJIO7R5EV/action/replication_record"}},"created_at":"2026-07-28T02:23:27.284463+00:00","updated_at":"2026-07-28T02:23:27.284463+00:00"}