{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:M5EZLHUVEAXASXZUYOXJ5Z3T4T","short_pith_number":"pith:M5EZLHUV","schema_version":"1.0","canonical_sha256":"6749959e95202e095f34c3ae9ee773e4dbe284d84849718455eabff9e0a07690","source":{"kind":"arxiv","id":"2202.11241","version":2},"attestation_state":"computed","paper":{"title":"FUNQUE: Fusion of Unified Quality Evaluators","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.IV"],"primary_cat":"cs.CV","authors_text":"Abhinau K. Venkataramanan, Alan C. Bovik, Cosmin Stejerean","submitted_at":"2022-02-23T00:21:43Z","abstract_excerpt":"Fusion-based quality assessment has emerged as a powerful method for developing high-performance quality models from quality models that individually achieve lower performances. A prominent example of such an algorithm is VMAF, which has been widely adopted as an industry standard for video quality prediction along with SSIM. In addition to advancing the state-of-the-art, it is imperative to alleviate the computational burden presented by the use of a heterogeneous set of quality models. In this paper, we unify \"atom\" quality models by computing them on a common transform domain that accounts "},"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":"2202.11241","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-02-23T00:21:43Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"7fac557bbce81c474ec2dc38bcbeb5d36ffe0897369e4008652373415959d1cc","abstract_canon_sha256":"e572236ac7b0ee8cf325d01fa3f0c1a7fd4b8ed4bc9a74896d1e273d2693a253"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:37:57.928616Z","signature_b64":"r/3FcjnvEfW+JWyuCkZmJ4e8zS19EoJ9WxdOka2Ho9f4Q1Jku7vcA8AuKfM3MGQa+y0TWNYMnUCs/J0mWWCZAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6749959e95202e095f34c3ae9ee773e4dbe284d84849718455eabff9e0a07690","last_reissued_at":"2026-07-05T04:37:57.928130Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:37:57.928130Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"FUNQUE: Fusion of Unified Quality Evaluators","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.IV"],"primary_cat":"cs.CV","authors_text":"Abhinau K. Venkataramanan, Alan C. Bovik, Cosmin Stejerean","submitted_at":"2022-02-23T00:21:43Z","abstract_excerpt":"Fusion-based quality assessment has emerged as a powerful method for developing high-performance quality models from quality models that individually achieve lower performances. A prominent example of such an algorithm is VMAF, which has been widely adopted as an industry standard for video quality prediction along with SSIM. In addition to advancing the state-of-the-art, it is imperative to alleviate the computational burden presented by the use of a heterogeneous set of quality models. In this paper, we unify \"atom\" quality models by computing them on a common transform domain that accounts "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.11241","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/2202.11241/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":"2202.11241","created_at":"2026-07-05T04:37:57.928195+00:00"},{"alias_kind":"arxiv_version","alias_value":"2202.11241v2","created_at":"2026-07-05T04:37:57.928195+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.11241","created_at":"2026-07-05T04:37:57.928195+00:00"},{"alias_kind":"pith_short_12","alias_value":"M5EZLHUVEAXA","created_at":"2026-07-05T04:37:57.928195+00:00"},{"alias_kind":"pith_short_16","alias_value":"M5EZLHUVEAXASXZU","created_at":"2026-07-05T04:37:57.928195+00:00"},{"alias_kind":"pith_short_8","alias_value":"M5EZLHUV","created_at":"2026-07-05T04:37:57.928195+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/M5EZLHUVEAXASXZUYOXJ5Z3T4T","json":"https://pith.science/pith/M5EZLHUVEAXASXZUYOXJ5Z3T4T.json","graph_json":"https://pith.science/api/pith-number/M5EZLHUVEAXASXZUYOXJ5Z3T4T/graph.json","events_json":"https://pith.science/api/pith-number/M5EZLHUVEAXASXZUYOXJ5Z3T4T/events.json","paper":"https://pith.science/paper/M5EZLHUV"},"agent_actions":{"view_html":"https://pith.science/pith/M5EZLHUVEAXASXZUYOXJ5Z3T4T","download_json":"https://pith.science/pith/M5EZLHUVEAXASXZUYOXJ5Z3T4T.json","view_paper":"https://pith.science/paper/M5EZLHUV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2202.11241&json=true","fetch_graph":"https://pith.science/api/pith-number/M5EZLHUVEAXASXZUYOXJ5Z3T4T/graph.json","fetch_events":"https://pith.science/api/pith-number/M5EZLHUVEAXASXZUYOXJ5Z3T4T/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/M5EZLHUVEAXASXZUYOXJ5Z3T4T/action/timestamp_anchor","attest_storage":"https://pith.science/pith/M5EZLHUVEAXASXZUYOXJ5Z3T4T/action/storage_attestation","attest_author":"https://pith.science/pith/M5EZLHUVEAXASXZUYOXJ5Z3T4T/action/author_attestation","sign_citation":"https://pith.science/pith/M5EZLHUVEAXASXZUYOXJ5Z3T4T/action/citation_signature","submit_replication":"https://pith.science/pith/M5EZLHUVEAXASXZUYOXJ5Z3T4T/action/replication_record"}},"created_at":"2026-07-05T04:37:57.928195+00:00","updated_at":"2026-07-05T04:37:57.928195+00:00"}