{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:KHFNDYH5357EUBPQ6FYIF2EJQ5","short_pith_number":"pith:KHFNDYH5","canonical_record":{"source":{"id":"2408.09241","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-08-17T16:26:59Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"ecdf3530d3ec43726c877e99275f0500880006801d6f92bea4c7a2ee861de3f8","abstract_canon_sha256":"2d2f69a31e283c2f730ff0a22f56e7d358533c78d3a3f734fa965070d63d828f"},"schema_version":"1.0"},"canonical_sha256":"51cad1e0fddf7e4a05f0f17082e8898741afe16ecca9a378ca12b8bbf2b27556","source":{"kind":"arxiv","id":"2408.09241","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.09241","created_at":"2026-07-05T11:36:21Z"},{"alias_kind":"arxiv_version","alias_value":"2408.09241v2","created_at":"2026-07-05T11:36:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.09241","created_at":"2026-07-05T11:36:21Z"},{"alias_kind":"pith_short_12","alias_value":"KHFNDYH5357E","created_at":"2026-07-05T11:36:21Z"},{"alias_kind":"pith_short_16","alias_value":"KHFNDYH5357EUBPQ","created_at":"2026-07-05T11:36:21Z"},{"alias_kind":"pith_short_8","alias_value":"KHFNDYH5","created_at":"2026-07-05T11:36:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:KHFNDYH5357EUBPQ6FYIF2EJQ5","target":"record","payload":{"canonical_record":{"source":{"id":"2408.09241","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-08-17T16:26:59Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"ecdf3530d3ec43726c877e99275f0500880006801d6f92bea4c7a2ee861de3f8","abstract_canon_sha256":"2d2f69a31e283c2f730ff0a22f56e7d358533c78d3a3f734fa965070d63d828f"},"schema_version":"1.0"},"canonical_sha256":"51cad1e0fddf7e4a05f0f17082e8898741afe16ecca9a378ca12b8bbf2b27556","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:36:21.343653Z","signature_b64":"DLkS333T7ZVVThvyeASCahRMsckZZI78jzDPjTFw/HseMhXDWxtLeZ0wfCFdzECr4nKPf3fV32Z8TcxiDG7SAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"51cad1e0fddf7e4a05f0f17082e8898741afe16ecca9a378ca12b8bbf2b27556","last_reissued_at":"2026-07-05T11:36:21.343143Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:36:21.343143Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.09241","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":"2026-07-05T11:36:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"siuEtykScBGi5bwVdrIjlZcC2vj7m7vsWdERgAi9G53J70T2NExDmEWzsz7fFIL7AwwFjsMsP9cYidMH6orPAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T06:57:47.844101Z"},"content_sha256":"961e19a723afb04b9aa960511a523d4ddeafb168a689de7d83a717176a922e4a","schema_version":"1.0","event_id":"sha256:961e19a723afb04b9aa960511a523d4ddeafb168a689de7d83a717176a922e4a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:KHFNDYH5357EUBPQ6FYIF2EJQ5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Re-boosting Self-Collaboration Parallel Prompt GAN for Unsupervised Image Restoration","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.IV"],"primary_cat":"cs.CV","authors_text":"Chao Ren, Jingtong Yue, Kelvin C.K. Chan, Lu Qi, Ming-Hsuan Yang, Xin Lin, Yuyan Zhou","submitted_at":"2024-08-17T16:26:59Z","abstract_excerpt":"Unsupervised restoration approaches based on generative adversarial networks (GANs) offer a promising solution without requiring paired datasets. Yet, these GAN-based approaches struggle to surpass the performance of conventional unsupervised GAN-based frameworks without significantly modifying model structures or increasing the computational complexity. To address these issues, we propose a self-collaboration (SC) strategy for existing restoration models. This strategy utilizes information from the previous stage as feedback to guide subsequent stages, achieving significant performance improv"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.09241","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/2408.09241/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":"2026-07-05T11:36:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RWKrahBpR+2FBu56uXeKW2TIplgZqlt3wCEoKcpU+C+OQSReiTSAo9BR27RvUqCjppsPubU0YDLyUGSXJoGPCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T06:57:47.844595Z"},"content_sha256":"fd953452249c723bae2f13b619cef4492d74d60c6931b1564db4266a85da9885","schema_version":"1.0","event_id":"sha256:fd953452249c723bae2f13b619cef4492d74d60c6931b1564db4266a85da9885"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KHFNDYH5357EUBPQ6FYIF2EJQ5/bundle.json","state_url":"https://pith.science/pith/KHFNDYH5357EUBPQ6FYIF2EJQ5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KHFNDYH5357EUBPQ6FYIF2EJQ5/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":"2026-08-17T06:57:47Z","links":{"resolver":"https://pith.science/pith/KHFNDYH5357EUBPQ6FYIF2EJQ5","bundle":"https://pith.science/pith/KHFNDYH5357EUBPQ6FYIF2EJQ5/bundle.json","state":"https://pith.science/pith/KHFNDYH5357EUBPQ6FYIF2EJQ5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KHFNDYH5357EUBPQ6FYIF2EJQ5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:KHFNDYH5357EUBPQ6FYIF2EJQ5","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":"2d2f69a31e283c2f730ff0a22f56e7d358533c78d3a3f734fa965070d63d828f","cross_cats_sorted":["eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-08-17T16:26:59Z","title_canon_sha256":"ecdf3530d3ec43726c877e99275f0500880006801d6f92bea4c7a2ee861de3f8"},"schema_version":"1.0","source":{"id":"2408.09241","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.09241","created_at":"2026-07-05T11:36:21Z"},{"alias_kind":"arxiv_version","alias_value":"2408.09241v2","created_at":"2026-07-05T11:36:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.09241","created_at":"2026-07-05T11:36:21Z"},{"alias_kind":"pith_short_12","alias_value":"KHFNDYH5357E","created_at":"2026-07-05T11:36:21Z"},{"alias_kind":"pith_short_16","alias_value":"KHFNDYH5357EUBPQ","created_at":"2026-07-05T11:36:21Z"},{"alias_kind":"pith_short_8","alias_value":"KHFNDYH5","created_at":"2026-07-05T11:36:21Z"}],"graph_snapshots":[{"event_id":"sha256:fd953452249c723bae2f13b619cef4492d74d60c6931b1564db4266a85da9885","target":"graph","created_at":"2026-07-05T11:36:21Z","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/2408.09241/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Unsupervised restoration approaches based on generative adversarial networks (GANs) offer a promising solution without requiring paired datasets. Yet, these GAN-based approaches struggle to surpass the performance of conventional unsupervised GAN-based frameworks without significantly modifying model structures or increasing the computational complexity. To address these issues, we propose a self-collaboration (SC) strategy for existing restoration models. This strategy utilizes information from the previous stage as feedback to guide subsequent stages, achieving significant performance improv","authors_text":"Chao Ren, Jingtong Yue, Kelvin C.K. Chan, Lu Qi, Ming-Hsuan Yang, Xin Lin, Yuyan Zhou","cross_cats":["eess.IV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-08-17T16:26:59Z","title":"Re-boosting Self-Collaboration Parallel Prompt GAN for Unsupervised Image Restoration"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.09241","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":"sha256:961e19a723afb04b9aa960511a523d4ddeafb168a689de7d83a717176a922e4a","target":"record","created_at":"2026-07-05T11:36:21Z","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":"2d2f69a31e283c2f730ff0a22f56e7d358533c78d3a3f734fa965070d63d828f","cross_cats_sorted":["eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-08-17T16:26:59Z","title_canon_sha256":"ecdf3530d3ec43726c877e99275f0500880006801d6f92bea4c7a2ee861de3f8"},"schema_version":"1.0","source":{"id":"2408.09241","kind":"arxiv","version":2}},"canonical_sha256":"51cad1e0fddf7e4a05f0f17082e8898741afe16ecca9a378ca12b8bbf2b27556","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"51cad1e0fddf7e4a05f0f17082e8898741afe16ecca9a378ca12b8bbf2b27556","first_computed_at":"2026-07-05T11:36:21.343143Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:36:21.343143Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"DLkS333T7ZVVThvyeASCahRMsckZZI78jzDPjTFw/HseMhXDWxtLeZ0wfCFdzECr4nKPf3fV32Z8TcxiDG7SAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:36:21.343653Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.09241","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:961e19a723afb04b9aa960511a523d4ddeafb168a689de7d83a717176a922e4a","sha256:fd953452249c723bae2f13b619cef4492d74d60c6931b1564db4266a85da9885"],"state_sha256":"56b6069e651972ae25216366b734287ef7e2bf1cfa549fba34bf030adb0d8f93"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ou3f2kndTogZc8Iz5RI49D16/WiuEFxsltqADX138UEQwmYWiHqR80rujxkXDPhQRzwprYKR+Rqn4Wknx1tSDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T06:57:47.849613Z","bundle_sha256":"74fa0dc1ffbb8a10826b49cab176b47c9cee7b55c8fcf42c109fcc963ce9c9ab"}}