{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:HAD3BXZWJMQDYHG5GK6GXWA3BG","short_pith_number":"pith:HAD3BXZW","schema_version":"1.0","canonical_sha256":"3807b0df364b203c1cdd32bc6bd81b09a6abc357b03c4619c4ca64d217e12d9e","source":{"kind":"arxiv","id":"2203.00845","version":1},"attestation_state":"computed","paper":{"title":"Can No-reference features help in Full-reference image quality estimation?","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CV"],"primary_cat":"eess.IV","authors_text":"Nisarg A. Shah, Saikat Dutta, Sourya Dipta Das","submitted_at":"2022-03-02T03:39:28Z","abstract_excerpt":"Development of perceptual image quality assessment (IQA) metrics has been of significant interest to computer vision community. The aim of these metrics is to model quality of an image as perceived by humans. Recent works in Full-reference IQA research perform pixelwise comparison between deep features corresponding to query and reference images for quality prediction. However, pixelwise feature comparison may not be meaningful if distortion present in query image is severe. In this context, we explore utilization of no-reference features in Full-reference IQA task. Our model consists of both "},"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":"2203.00845","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-03-02T03:39:28Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"ee18d55013d6c04fd591a233f1cbbafe2dacefd9dd80b261b4fde228d74d98b2","abstract_canon_sha256":"09c8dfbb8df9cb982d891eac4863aac6ac91b7927edfada8f2cd1fd3542f9700"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:01:24.056096Z","signature_b64":"QbdlhsS1XbdPPDjybO33QJ0gqQtnR/sGUasxKprmUqGAZWcDpAU1gl1+nL4y0yUlpI1CwW/roWwRY5qcjsKsCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3807b0df364b203c1cdd32bc6bd81b09a6abc357b03c4619c4ca64d217e12d9e","last_reissued_at":"2026-07-05T04:01:24.055603Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:01:24.055603Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Can No-reference features help in Full-reference image quality estimation?","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CV"],"primary_cat":"eess.IV","authors_text":"Nisarg A. Shah, Saikat Dutta, Sourya Dipta Das","submitted_at":"2022-03-02T03:39:28Z","abstract_excerpt":"Development of perceptual image quality assessment (IQA) metrics has been of significant interest to computer vision community. The aim of these metrics is to model quality of an image as perceived by humans. Recent works in Full-reference IQA research perform pixelwise comparison between deep features corresponding to query and reference images for quality prediction. However, pixelwise feature comparison may not be meaningful if distortion present in query image is severe. In this context, we explore utilization of no-reference features in Full-reference IQA task. Our model consists of both "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.00845","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/2203.00845/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":"2203.00845","created_at":"2026-07-05T04:01:24.055664+00:00"},{"alias_kind":"arxiv_version","alias_value":"2203.00845v1","created_at":"2026-07-05T04:01:24.055664+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.00845","created_at":"2026-07-05T04:01:24.055664+00:00"},{"alias_kind":"pith_short_12","alias_value":"HAD3BXZWJMQD","created_at":"2026-07-05T04:01:24.055664+00:00"},{"alias_kind":"pith_short_16","alias_value":"HAD3BXZWJMQDYHG5","created_at":"2026-07-05T04:01:24.055664+00:00"},{"alias_kind":"pith_short_8","alias_value":"HAD3BXZW","created_at":"2026-07-05T04:01:24.055664+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/HAD3BXZWJMQDYHG5GK6GXWA3BG","json":"https://pith.science/pith/HAD3BXZWJMQDYHG5GK6GXWA3BG.json","graph_json":"https://pith.science/api/pith-number/HAD3BXZWJMQDYHG5GK6GXWA3BG/graph.json","events_json":"https://pith.science/api/pith-number/HAD3BXZWJMQDYHG5GK6GXWA3BG/events.json","paper":"https://pith.science/paper/HAD3BXZW"},"agent_actions":{"view_html":"https://pith.science/pith/HAD3BXZWJMQDYHG5GK6GXWA3BG","download_json":"https://pith.science/pith/HAD3BXZWJMQDYHG5GK6GXWA3BG.json","view_paper":"https://pith.science/paper/HAD3BXZW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2203.00845&json=true","fetch_graph":"https://pith.science/api/pith-number/HAD3BXZWJMQDYHG5GK6GXWA3BG/graph.json","fetch_events":"https://pith.science/api/pith-number/HAD3BXZWJMQDYHG5GK6GXWA3BG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HAD3BXZWJMQDYHG5GK6GXWA3BG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HAD3BXZWJMQDYHG5GK6GXWA3BG/action/storage_attestation","attest_author":"https://pith.science/pith/HAD3BXZWJMQDYHG5GK6GXWA3BG/action/author_attestation","sign_citation":"https://pith.science/pith/HAD3BXZWJMQDYHG5GK6GXWA3BG/action/citation_signature","submit_replication":"https://pith.science/pith/HAD3BXZWJMQDYHG5GK6GXWA3BG/action/replication_record"}},"created_at":"2026-07-05T04:01:24.055664+00:00","updated_at":"2026-07-05T04:01:24.055664+00:00"}