{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:XO5MTZEW72COGOAIL3UQDJMWDR","short_pith_number":"pith:XO5MTZEW","canonical_record":{"source":{"id":"2108.08697","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-08-19T14:04:59Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"ed9140c9abc64900e29de3f8fab7bddceba05c0a6242858071b2e9f0738f0046","abstract_canon_sha256":"fb0ef4222709b97ad204dbe5c38750c2684336688940535f7bb67d784886f62d"},"schema_version":"1.0"},"canonical_sha256":"bbbac9e496fe84e338085ee901a5961c7505429db4920803db301f0a2bcad70a","source":{"kind":"arxiv","id":"2108.08697","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2108.08697","created_at":"2026-07-05T03:07:12Z"},{"alias_kind":"arxiv_version","alias_value":"2108.08697v1","created_at":"2026-07-05T03:07:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2108.08697","created_at":"2026-07-05T03:07:12Z"},{"alias_kind":"pith_short_12","alias_value":"XO5MTZEW72CO","created_at":"2026-07-05T03:07:12Z"},{"alias_kind":"pith_short_16","alias_value":"XO5MTZEW72COGOAI","created_at":"2026-07-05T03:07:12Z"},{"alias_kind":"pith_short_8","alias_value":"XO5MTZEW","created_at":"2026-07-05T03:07:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:XO5MTZEW72COGOAIL3UQDJMWDR","target":"record","payload":{"canonical_record":{"source":{"id":"2108.08697","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-08-19T14:04:59Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"ed9140c9abc64900e29de3f8fab7bddceba05c0a6242858071b2e9f0738f0046","abstract_canon_sha256":"fb0ef4222709b97ad204dbe5c38750c2684336688940535f7bb67d784886f62d"},"schema_version":"1.0"},"canonical_sha256":"bbbac9e496fe84e338085ee901a5961c7505429db4920803db301f0a2bcad70a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:07:12.631969Z","signature_b64":"/0nR6NWnnr6hcOjLpgxOT9myiHRgVJMBoZVSwVo7qYbYcRAqEDxCrb/ip1bByupoy/wdNziZZnavFfw48dp/Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bbbac9e496fe84e338085ee901a5961c7505429db4920803db301f0a2bcad70a","last_reissued_at":"2026-07-05T03:07:12.631514Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:07:12.631514Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2108.08697","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":"2026-07-05T03:07:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mVzJLslrO6QRDc72KKv0sedwjzWaFes0PZYdGC6zDs4NZZbV84VwT32iDzRxBUSvMecRuy7sjoN6BBjP+LXnDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T06:25:48.601738Z"},"content_sha256":"11982f3f199e2de49785f0ca8e3fa2ffbeeec5f1b7c4986c74fe4c120ee569ac","schema_version":"1.0","event_id":"sha256:11982f3f199e2de49785f0ca8e3fa2ffbeeec5f1b7c4986c74fe4c120ee569ac"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:XO5MTZEW72COGOAIL3UQDJMWDR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Real-time Image Enhancer via Learnable Spatial-aware 3D Lookup Tables","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.IV"],"primary_cat":"cs.CV","authors_text":"Fenglong Song, Jingyang Peng, Tao Wang, Xian Wang, Yipeng Ma, Yong Li, Youliang Yan","submitted_at":"2021-08-19T14:04:59Z","abstract_excerpt":"Recently, deep learning-based image enhancement algorithms achieved state-of-the-art (SOTA) performance on several publicly available datasets. However, most existing methods fail to meet practical requirements either for visual perception or for computation efficiency, especially for high-resolution images. In this paper, we propose a novel real-time image enhancer via learnable spatial-aware 3-dimentional lookup tables(3D LUTs), which well considers global scenario and local spatial information. Specifically, we introduce a light weight two-head weight predictor that has two outputs. One is "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2108.08697","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/2108.08697/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":"2026-07-05T03:07:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bzFA80KjgOAYY0m/U01d4a3h1dpwaw3m1bJVjDLxuOh3mXzWASeRR20xsaCZR5aAsXExnbxIQv3GlXhSgIPVCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T06:25:48.602396Z"},"content_sha256":"f33a29a8f9f8be919fd24ccedd5de1e11e06cfafbd817f7b9c3f7657bdc4ff29","schema_version":"1.0","event_id":"sha256:f33a29a8f9f8be919fd24ccedd5de1e11e06cfafbd817f7b9c3f7657bdc4ff29"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XO5MTZEW72COGOAIL3UQDJMWDR/bundle.json","state_url":"https://pith.science/pith/XO5MTZEW72COGOAIL3UQDJMWDR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XO5MTZEW72COGOAIL3UQDJMWDR/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":"2026-08-15T06:25:48Z","links":{"resolver":"https://pith.science/pith/XO5MTZEW72COGOAIL3UQDJMWDR","bundle":"https://pith.science/pith/XO5MTZEW72COGOAIL3UQDJMWDR/bundle.json","state":"https://pith.science/pith/XO5MTZEW72COGOAIL3UQDJMWDR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XO5MTZEW72COGOAIL3UQDJMWDR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:XO5MTZEW72COGOAIL3UQDJMWDR","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":"fb0ef4222709b97ad204dbe5c38750c2684336688940535f7bb67d784886f62d","cross_cats_sorted":["eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-08-19T14:04:59Z","title_canon_sha256":"ed9140c9abc64900e29de3f8fab7bddceba05c0a6242858071b2e9f0738f0046"},"schema_version":"1.0","source":{"id":"2108.08697","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2108.08697","created_at":"2026-07-05T03:07:12Z"},{"alias_kind":"arxiv_version","alias_value":"2108.08697v1","created_at":"2026-07-05T03:07:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2108.08697","created_at":"2026-07-05T03:07:12Z"},{"alias_kind":"pith_short_12","alias_value":"XO5MTZEW72CO","created_at":"2026-07-05T03:07:12Z"},{"alias_kind":"pith_short_16","alias_value":"XO5MTZEW72COGOAI","created_at":"2026-07-05T03:07:12Z"},{"alias_kind":"pith_short_8","alias_value":"XO5MTZEW","created_at":"2026-07-05T03:07:12Z"}],"graph_snapshots":[{"event_id":"sha256:f33a29a8f9f8be919fd24ccedd5de1e11e06cfafbd817f7b9c3f7657bdc4ff29","target":"graph","created_at":"2026-07-05T03:07:12Z","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/2108.08697/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recently, deep learning-based image enhancement algorithms achieved state-of-the-art (SOTA) performance on several publicly available datasets. However, most existing methods fail to meet practical requirements either for visual perception or for computation efficiency, especially for high-resolution images. In this paper, we propose a novel real-time image enhancer via learnable spatial-aware 3-dimentional lookup tables(3D LUTs), which well considers global scenario and local spatial information. Specifically, we introduce a light weight two-head weight predictor that has two outputs. One is ","authors_text":"Fenglong Song, Jingyang Peng, Tao Wang, Xian Wang, Yipeng Ma, Yong Li, Youliang Yan","cross_cats":["eess.IV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-08-19T14:04:59Z","title":"Real-time Image Enhancer via Learnable Spatial-aware 3D Lookup Tables"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2108.08697","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":"sha256:11982f3f199e2de49785f0ca8e3fa2ffbeeec5f1b7c4986c74fe4c120ee569ac","target":"record","created_at":"2026-07-05T03:07:12Z","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":"fb0ef4222709b97ad204dbe5c38750c2684336688940535f7bb67d784886f62d","cross_cats_sorted":["eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-08-19T14:04:59Z","title_canon_sha256":"ed9140c9abc64900e29de3f8fab7bddceba05c0a6242858071b2e9f0738f0046"},"schema_version":"1.0","source":{"id":"2108.08697","kind":"arxiv","version":1}},"canonical_sha256":"bbbac9e496fe84e338085ee901a5961c7505429db4920803db301f0a2bcad70a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bbbac9e496fe84e338085ee901a5961c7505429db4920803db301f0a2bcad70a","first_computed_at":"2026-07-05T03:07:12.631514Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:07:12.631514Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/0nR6NWnnr6hcOjLpgxOT9myiHRgVJMBoZVSwVo7qYbYcRAqEDxCrb/ip1bByupoy/wdNziZZnavFfw48dp/Cg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:07:12.631969Z","signed_message":"canonical_sha256_bytes"},"source_id":"2108.08697","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:11982f3f199e2de49785f0ca8e3fa2ffbeeec5f1b7c4986c74fe4c120ee569ac","sha256:f33a29a8f9f8be919fd24ccedd5de1e11e06cfafbd817f7b9c3f7657bdc4ff29"],"state_sha256":"fcd9993e264fd62e5f6fe9b6dac568591a44ed08e7b14b437f6fb1c4ddc6a400"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6jsLadaZ6tgCoccJfPyFAbrL9SNa81j5tlXyKJ2chKMUaelxK+DReA5NdCuAnD2YMaj50TOtjpgFTAT0biF0Cg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-15T06:25:48.609853Z","bundle_sha256":"b978543f72205e68c953598f228d0f97b7064f650cf8306341e0b272eb738b03"}}