{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:ENBJKQ6C4DT4LH7SNANXF53C5N","short_pith_number":"pith:ENBJKQ6C","canonical_record":{"source":{"id":"1711.06787","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-18T01:37:04Z","cross_cats_sorted":[],"title_canon_sha256":"d2bc538b000394a59627cb7cb8afcae9fce377b13b415100820b8660cca2d921","abstract_canon_sha256":"888a4a6faaf51f984d7f8beff41cd3026b6b753b8e96558124da8bf1083c44c0"},"schema_version":"1.0"},"canonical_sha256":"23429543c2e0e7c59ff2681b72f762eb48175de3913214bf9dd11e542057a711","source":{"kind":"arxiv","id":"1711.06787","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.06787","created_at":"2026-05-18T00:09:30Z"},{"alias_kind":"arxiv_version","alias_value":"1711.06787v2","created_at":"2026-05-18T00:09:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.06787","created_at":"2026-05-18T00:09:30Z"},{"alias_kind":"pith_short_12","alias_value":"ENBJKQ6C4DT4","created_at":"2026-05-18T12:31:12Z"},{"alias_kind":"pith_short_16","alias_value":"ENBJKQ6C4DT4LH7S","created_at":"2026-05-18T12:31:12Z"},{"alias_kind":"pith_short_8","alias_value":"ENBJKQ6C","created_at":"2026-05-18T12:31:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:ENBJKQ6C4DT4LH7SNANXF53C5N","target":"record","payload":{"canonical_record":{"source":{"id":"1711.06787","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-18T01:37:04Z","cross_cats_sorted":[],"title_canon_sha256":"d2bc538b000394a59627cb7cb8afcae9fce377b13b415100820b8660cca2d921","abstract_canon_sha256":"888a4a6faaf51f984d7f8beff41cd3026b6b753b8e96558124da8bf1083c44c0"},"schema_version":"1.0"},"canonical_sha256":"23429543c2e0e7c59ff2681b72f762eb48175de3913214bf9dd11e542057a711","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:09:30.266304Z","signature_b64":"qLhQER35XsAPHo1cKBsrB3/GcDHpoc3Q3xU7vTd1HXtPzA+EFRB02SLVOmFgYV/2tHFyeNNlxQgjgjHAu1AbCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"23429543c2e0e7c59ff2681b72f762eb48175de3913214bf9dd11e542057a711","last_reissued_at":"2026-05-18T00:09:30.265641Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:09:30.265641Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1711.06787","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":"2026-05-18T00:09:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"19/Bo2pKl5sZa8YTFnHk8AjpU5rHHQ3tZbkP71LDtM783ed14DVdLwVII73M6zshLgo9bb+mAgcrVS+PxnXLDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T17:33:43.898355Z"},"content_sha256":"386ef6fdb95141f457ae4b59f7957f4dbb9531186fa477e90f7d295291c515c0","schema_version":"1.0","event_id":"sha256:386ef6fdb95141f457ae4b59f7957f4dbb9531186fa477e90f7d295291c515c0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:ENBJKQ6C4DT4LH7SNANXF53C5N","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning Aggregated Transmission Propagation Networks for Haze Removal and Beyond","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Lei Zhang, Minjun Hou, Risheng Liu, Xin Fan, Zhiying Jiang, Zhongxuan Luo","submitted_at":"2017-11-18T01:37:04Z","abstract_excerpt":"Single image dehazing is an important low-level vision task with many applications. Early researches have investigated different kinds of visual priors to address this problem. However, they may fail when their assumptions are not valid on specific images. Recent deep networks also achieve relatively good performance in this task. But unfortunately, due to the disappreciation of rich physical rules in hazes, large amounts of data are required for their training. More importantly, they may still fail when there exist completely different haze distributions in testing images. By considering the "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.06787","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":""},"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":"2026-05-18T00:09:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IuAWXfntliwMcgxSHsrvgwTGa+k2z6qbEDDp+/sBfCqbL55jMmVgCdwrhqAdFQNSdk+y4f1GZhvCv5vdkQvWAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T17:33:43.898703Z"},"content_sha256":"bcfc7d5392736d5bb9fd9f74f99e4c1a14061d45b9baedfe189e9284a65bdcd1","schema_version":"1.0","event_id":"sha256:bcfc7d5392736d5bb9fd9f74f99e4c1a14061d45b9baedfe189e9284a65bdcd1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ENBJKQ6C4DT4LH7SNANXF53C5N/bundle.json","state_url":"https://pith.science/pith/ENBJKQ6C4DT4LH7SNANXF53C5N/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ENBJKQ6C4DT4LH7SNANXF53C5N/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":"2026-06-05T17:33:43Z","links":{"resolver":"https://pith.science/pith/ENBJKQ6C4DT4LH7SNANXF53C5N","bundle":"https://pith.science/pith/ENBJKQ6C4DT4LH7SNANXF53C5N/bundle.json","state":"https://pith.science/pith/ENBJKQ6C4DT4LH7SNANXF53C5N/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ENBJKQ6C4DT4LH7SNANXF53C5N/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:ENBJKQ6C4DT4LH7SNANXF53C5N","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":"888a4a6faaf51f984d7f8beff41cd3026b6b753b8e96558124da8bf1083c44c0","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-18T01:37:04Z","title_canon_sha256":"d2bc538b000394a59627cb7cb8afcae9fce377b13b415100820b8660cca2d921"},"schema_version":"1.0","source":{"id":"1711.06787","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.06787","created_at":"2026-05-18T00:09:30Z"},{"alias_kind":"arxiv_version","alias_value":"1711.06787v2","created_at":"2026-05-18T00:09:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.06787","created_at":"2026-05-18T00:09:30Z"},{"alias_kind":"pith_short_12","alias_value":"ENBJKQ6C4DT4","created_at":"2026-05-18T12:31:12Z"},{"alias_kind":"pith_short_16","alias_value":"ENBJKQ6C4DT4LH7S","created_at":"2026-05-18T12:31:12Z"},{"alias_kind":"pith_short_8","alias_value":"ENBJKQ6C","created_at":"2026-05-18T12:31:12Z"}],"graph_snapshots":[{"event_id":"sha256:bcfc7d5392736d5bb9fd9f74f99e4c1a14061d45b9baedfe189e9284a65bdcd1","target":"graph","created_at":"2026-05-18T00:09:30Z","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"},"paper":{"abstract_excerpt":"Single image dehazing is an important low-level vision task with many applications. Early researches have investigated different kinds of visual priors to address this problem. However, they may fail when their assumptions are not valid on specific images. Recent deep networks also achieve relatively good performance in this task. But unfortunately, due to the disappreciation of rich physical rules in hazes, large amounts of data are required for their training. More importantly, they may still fail when there exist completely different haze distributions in testing images. By considering the ","authors_text":"Lei Zhang, Minjun Hou, Risheng Liu, Xin Fan, Zhiying Jiang, Zhongxuan Luo","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-18T01:37:04Z","title":"Learning Aggregated Transmission Propagation Networks for Haze Removal and Beyond"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.06787","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":"sha256:386ef6fdb95141f457ae4b59f7957f4dbb9531186fa477e90f7d295291c515c0","target":"record","created_at":"2026-05-18T00:09:30Z","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":"888a4a6faaf51f984d7f8beff41cd3026b6b753b8e96558124da8bf1083c44c0","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-18T01:37:04Z","title_canon_sha256":"d2bc538b000394a59627cb7cb8afcae9fce377b13b415100820b8660cca2d921"},"schema_version":"1.0","source":{"id":"1711.06787","kind":"arxiv","version":2}},"canonical_sha256":"23429543c2e0e7c59ff2681b72f762eb48175de3913214bf9dd11e542057a711","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"23429543c2e0e7c59ff2681b72f762eb48175de3913214bf9dd11e542057a711","first_computed_at":"2026-05-18T00:09:30.265641Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:09:30.265641Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qLhQER35XsAPHo1cKBsrB3/GcDHpoc3Q3xU7vTd1HXtPzA+EFRB02SLVOmFgYV/2tHFyeNNlxQgjgjHAu1AbCA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:09:30.266304Z","signed_message":"canonical_sha256_bytes"},"source_id":"1711.06787","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:386ef6fdb95141f457ae4b59f7957f4dbb9531186fa477e90f7d295291c515c0","sha256:bcfc7d5392736d5bb9fd9f74f99e4c1a14061d45b9baedfe189e9284a65bdcd1"],"state_sha256":"57c2332a45a3741a6365890435bafd211fab75354359a8932fd52b5032c50137"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wf59qYQZIihjPSNEpEq+JopldLu1VRGU+R3qcPAAKkcbis81vPGQfhLb8LoT4ER1xAS+jthztn7qCcJpk49GBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-05T17:33:43.900733Z","bundle_sha256":"b70b9cc73b3e8a0ec0afa1ec7529a3d8e12b35d0c1815dd3cedabe81bcbdcb5e"}}