{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:UQXG7AGSXCOSLYHWNHZD6YWO2K","short_pith_number":"pith:UQXG7AGS","canonical_record":{"source":{"id":"2407.11750","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-07-16T14:16:42Z","cross_cats_sorted":[],"title_canon_sha256":"60eea423a5bfaebabfb53efd1891b73637244505097f7557c35020ff86bef4e9","abstract_canon_sha256":"66537421e620602aeda02c05d30cfb126960fe2f209f5c449713407ac7f4e49a"},"schema_version":"1.0"},"canonical_sha256":"a42e6f80d2b89d25e0f669f23f62ced29f4619120e5b8e8e0d0fc801e11ec044","source":{"kind":"arxiv","id":"2407.11750","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.11750","created_at":"2026-07-05T08:44:40Z"},{"alias_kind":"arxiv_version","alias_value":"2407.11750v1","created_at":"2026-07-05T08:44:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.11750","created_at":"2026-07-05T08:44:40Z"},{"alias_kind":"pith_short_12","alias_value":"UQXG7AGSXCOS","created_at":"2026-07-05T08:44:40Z"},{"alias_kind":"pith_short_16","alias_value":"UQXG7AGSXCOSLYHW","created_at":"2026-07-05T08:44:40Z"},{"alias_kind":"pith_short_8","alias_value":"UQXG7AGS","created_at":"2026-07-05T08:44:40Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:UQXG7AGSXCOSLYHWNHZD6YWO2K","target":"record","payload":{"canonical_record":{"source":{"id":"2407.11750","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-07-16T14:16:42Z","cross_cats_sorted":[],"title_canon_sha256":"60eea423a5bfaebabfb53efd1891b73637244505097f7557c35020ff86bef4e9","abstract_canon_sha256":"66537421e620602aeda02c05d30cfb126960fe2f209f5c449713407ac7f4e49a"},"schema_version":"1.0"},"canonical_sha256":"a42e6f80d2b89d25e0f669f23f62ced29f4619120e5b8e8e0d0fc801e11ec044","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:44:40.421279Z","signature_b64":"6e2Ndg6pVyBLg0r+ye5dqvDyC5DSFFewRQHJrAIb0et7BfnSj5uVs2D/g4OaG2jzHJ2PFx7uLwhE5xIIAR9SBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a42e6f80d2b89d25e0f669f23f62ced29f4619120e5b8e8e0d0fc801e11ec044","last_reissued_at":"2026-07-05T08:44:40.420725Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:44:40.420725Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2407.11750","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:44:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/gv3IT6B82OVRKe/0ohyx4SEMTBV3IYSU/R3LZWvp+Is5b+/9o+bn/QSPDAfTmxV9GYmseXru0NonUn39q95BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-12T19:57:01.192366Z"},"content_sha256":"d6bbea92acbe4ccb724810dc5a179bafd94c9480961c34d13e0bd62714987d2c","schema_version":"1.0","event_id":"sha256:d6bbea92acbe4ccb724810dc5a179bafd94c9480961c34d13e0bd62714987d2c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:UQXG7AGSXCOSLYHWNHZD6YWO2K","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Cycle Contrastive Adversarial Learning for Unsupervised image Deraining","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chengwei Hu, Chen Zhao, Weiling Cai, Zheng Yuan","submitted_at":"2024-07-16T14:16:42Z","abstract_excerpt":"To tackle the difficulties in fitting paired real-world data for single image deraining (SID), recent unsupervised methods have achieved notable success. However, these methods often struggle to generate high-quality, rain-free images due to a lack of attention to semantic representation and image content, resulting in ineffective separation of content from the rain layer. In this paper, we propose a novel cycle contrastive generative adversarial network for unsupervised SID, called CCLGAN. This framework combines cycle contrastive learning (CCL) and location contrastive learning (LCL). CCL im"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.11750","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/2407.11750/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":"2026-07-05T08:44:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"W5EiIWc82jUxX8mwvsKg/oCvbte77EbZzaiOFk1bf3Y3kXmpy8AcciP0zPSvODDx+lBMi/jpN97XqSQmd22ZCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-12T19:57:01.193039Z"},"content_sha256":"d29e7f68d7fc9c8b5438bbb4f02b2fb7d794a17963788a8797d651ade2ac7f99","schema_version":"1.0","event_id":"sha256:d29e7f68d7fc9c8b5438bbb4f02b2fb7d794a17963788a8797d651ade2ac7f99"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UQXG7AGSXCOSLYHWNHZD6YWO2K/bundle.json","state_url":"https://pith.science/pith/UQXG7AGSXCOSLYHWNHZD6YWO2K/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UQXG7AGSXCOSLYHWNHZD6YWO2K/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":"2026-07-12T19:57:01Z","links":{"resolver":"https://pith.science/pith/UQXG7AGSXCOSLYHWNHZD6YWO2K","bundle":"https://pith.science/pith/UQXG7AGSXCOSLYHWNHZD6YWO2K/bundle.json","state":"https://pith.science/pith/UQXG7AGSXCOSLYHWNHZD6YWO2K/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UQXG7AGSXCOSLYHWNHZD6YWO2K/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:UQXG7AGSXCOSLYHWNHZD6YWO2K","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":"66537421e620602aeda02c05d30cfb126960fe2f209f5c449713407ac7f4e49a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-07-16T14:16:42Z","title_canon_sha256":"60eea423a5bfaebabfb53efd1891b73637244505097f7557c35020ff86bef4e9"},"schema_version":"1.0","source":{"id":"2407.11750","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.11750","created_at":"2026-07-05T08:44:40Z"},{"alias_kind":"arxiv_version","alias_value":"2407.11750v1","created_at":"2026-07-05T08:44:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.11750","created_at":"2026-07-05T08:44:40Z"},{"alias_kind":"pith_short_12","alias_value":"UQXG7AGSXCOS","created_at":"2026-07-05T08:44:40Z"},{"alias_kind":"pith_short_16","alias_value":"UQXG7AGSXCOSLYHW","created_at":"2026-07-05T08:44:40Z"},{"alias_kind":"pith_short_8","alias_value":"UQXG7AGS","created_at":"2026-07-05T08:44:40Z"}],"graph_snapshots":[{"event_id":"sha256:d29e7f68d7fc9c8b5438bbb4f02b2fb7d794a17963788a8797d651ade2ac7f99","target":"graph","created_at":"2026-07-05T08:44:40Z","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/2407.11750/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"To tackle the difficulties in fitting paired real-world data for single image deraining (SID), recent unsupervised methods have achieved notable success. However, these methods often struggle to generate high-quality, rain-free images due to a lack of attention to semantic representation and image content, resulting in ineffective separation of content from the rain layer. In this paper, we propose a novel cycle contrastive generative adversarial network for unsupervised SID, called CCLGAN. This framework combines cycle contrastive learning (CCL) and location contrastive learning (LCL). CCL im","authors_text":"Chengwei Hu, Chen Zhao, Weiling Cai, Zheng Yuan","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-07-16T14:16:42Z","title":"Cycle Contrastive Adversarial Learning for Unsupervised image Deraining"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.11750","kind":"arxiv","version":1},"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:d6bbea92acbe4ccb724810dc5a179bafd94c9480961c34d13e0bd62714987d2c","target":"record","created_at":"2026-07-05T08:44:40Z","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":"66537421e620602aeda02c05d30cfb126960fe2f209f5c449713407ac7f4e49a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-07-16T14:16:42Z","title_canon_sha256":"60eea423a5bfaebabfb53efd1891b73637244505097f7557c35020ff86bef4e9"},"schema_version":"1.0","source":{"id":"2407.11750","kind":"arxiv","version":1}},"canonical_sha256":"a42e6f80d2b89d25e0f669f23f62ced29f4619120e5b8e8e0d0fc801e11ec044","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a42e6f80d2b89d25e0f669f23f62ced29f4619120e5b8e8e0d0fc801e11ec044","first_computed_at":"2026-07-05T08:44:40.420725Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:44:40.420725Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6e2Ndg6pVyBLg0r+ye5dqvDyC5DSFFewRQHJrAIb0et7BfnSj5uVs2D/g4OaG2jzHJ2PFx7uLwhE5xIIAR9SBA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:44:40.421279Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.11750","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d6bbea92acbe4ccb724810dc5a179bafd94c9480961c34d13e0bd62714987d2c","sha256:d29e7f68d7fc9c8b5438bbb4f02b2fb7d794a17963788a8797d651ade2ac7f99"],"state_sha256":"30192090c6ec837672c403c9663db713eeaae01008b38063438a037d64bfe1d5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"p9oFeOE5plnd+X8fN3cUpEjywEqD63uBMystz1oa5Xy4VgGhFwOYGj5ZAZtMb7hT+XCdoneiup3dv9d52TaWBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-12T19:57:01.196666Z","bundle_sha256":"912fd0cd2cb474e6a0618e18e69a0e6126361e8bc6aafb34151786efebe5389b"}}