{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:424RI2ZSBXQ5H5CRA4LLFA5RZJ","short_pith_number":"pith:424RI2ZS","canonical_record":{"source":{"id":"1911.09930","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-11-22T09:00:55Z","cross_cats_sorted":[],"title_canon_sha256":"2245209c09ce61da4c1eb56b719a1be1cc8d37a0e62c40dbc499b2319a6c00e6","abstract_canon_sha256":"2ae81f57a9fe11d9253e7d0ca782d88c332816e7aef125288843649436c87762"},"schema_version":"1.0"},"canonical_sha256":"e6b9146b320de1d3f4510716b283b1ca47b1c590ac94ac080e774c4952e8de0f","source":{"kind":"arxiv","id":"1911.09930","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1911.09930","created_at":"2026-07-05T01:06:09Z"},{"alias_kind":"arxiv_version","alias_value":"1911.09930v2","created_at":"2026-07-05T01:06:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1911.09930","created_at":"2026-07-05T01:06:09Z"},{"alias_kind":"pith_short_12","alias_value":"424RI2ZSBXQ5","created_at":"2026-07-05T01:06:09Z"},{"alias_kind":"pith_short_16","alias_value":"424RI2ZSBXQ5H5CR","created_at":"2026-07-05T01:06:09Z"},{"alias_kind":"pith_short_8","alias_value":"424RI2ZS","created_at":"2026-07-05T01:06:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:424RI2ZSBXQ5H5CRA4LLFA5RZJ","target":"record","payload":{"canonical_record":{"source":{"id":"1911.09930","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-11-22T09:00:55Z","cross_cats_sorted":[],"title_canon_sha256":"2245209c09ce61da4c1eb56b719a1be1cc8d37a0e62c40dbc499b2319a6c00e6","abstract_canon_sha256":"2ae81f57a9fe11d9253e7d0ca782d88c332816e7aef125288843649436c87762"},"schema_version":"1.0"},"canonical_sha256":"e6b9146b320de1d3f4510716b283b1ca47b1c590ac94ac080e774c4952e8de0f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:06:09.465093Z","signature_b64":"ij81WWGej1HwFsz3XP/J6dJIpH0Msx+w+d3Mfb14uaekA7WpyUYTGGsJ/HAODp5CWnQ9jnQ+oGT1/HrIGtfzBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e6b9146b320de1d3f4510716b283b1ca47b1c590ac94ac080e774c4952e8de0f","last_reissued_at":"2026-07-05T01:06:09.464521Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:06:09.464521Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1911.09930","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":"2026-07-05T01:06:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZdNgKMaZYl0TGlkQNdbr0y+Ik3WQfJYh6QcP0iMYql+0+KSPrv+QbZKhmL+QA2Y0f1EzPj9nMS/aq1PJihV4Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-20T18:46:07.092514Z"},"content_sha256":"07596cf3541743efd2f6f93acde08c3c15a1c6f6e460c35f438745fbe5851179","schema_version":"1.0","event_id":"sha256:07596cf3541743efd2f6f93acde08c3c15a1c6f6e460c35f438745fbe5851179"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:424RI2ZSBXQ5H5CRA4LLFA5RZJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Unsupervised Learning for Intrinsic Image Decomposition from a Single Image","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Feng Lu, Shaodi You, Yu Li, Yunfei Liu","submitted_at":"2019-11-22T09:00:55Z","abstract_excerpt":"Intrinsic image decomposition, which is an essential task in computer vision, aims to infer the reflectance and shading of the scene. It is challenging since it needs to separate one image into two components. To tackle this, conventional methods introduce various priors to constrain the solution, yet with limited performance. Meanwhile, the problem is typically solved by supervised learning methods, which is actually not an ideal solution since obtaining ground truth reflectance and shading for massive general natural scenes is challenging and even impossible. In this paper, we propose a nove"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1911.09930","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/1911.09930/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":"2026-07-05T01:06:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/SvEduA0Xi2ynLtUYibft4ohrwWm61INEQ+O/i7gAC2Sgckfch7igUS6xQqfGNyVmytsU2oydw8pNh920uwDBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-20T18:46:07.092897Z"},"content_sha256":"061a83f78c98d98c644993ed88ef51b156f29816aa2bb57f18df4211a8c1accd","schema_version":"1.0","event_id":"sha256:061a83f78c98d98c644993ed88ef51b156f29816aa2bb57f18df4211a8c1accd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/424RI2ZSBXQ5H5CRA4LLFA5RZJ/bundle.json","state_url":"https://pith.science/pith/424RI2ZSBXQ5H5CRA4LLFA5RZJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/424RI2ZSBXQ5H5CRA4LLFA5RZJ/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":"2026-07-20T18:46:07Z","links":{"resolver":"https://pith.science/pith/424RI2ZSBXQ5H5CRA4LLFA5RZJ","bundle":"https://pith.science/pith/424RI2ZSBXQ5H5CRA4LLFA5RZJ/bundle.json","state":"https://pith.science/pith/424RI2ZSBXQ5H5CRA4LLFA5RZJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/424RI2ZSBXQ5H5CRA4LLFA5RZJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:424RI2ZSBXQ5H5CRA4LLFA5RZJ","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":"2ae81f57a9fe11d9253e7d0ca782d88c332816e7aef125288843649436c87762","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-11-22T09:00:55Z","title_canon_sha256":"2245209c09ce61da4c1eb56b719a1be1cc8d37a0e62c40dbc499b2319a6c00e6"},"schema_version":"1.0","source":{"id":"1911.09930","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1911.09930","created_at":"2026-07-05T01:06:09Z"},{"alias_kind":"arxiv_version","alias_value":"1911.09930v2","created_at":"2026-07-05T01:06:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1911.09930","created_at":"2026-07-05T01:06:09Z"},{"alias_kind":"pith_short_12","alias_value":"424RI2ZSBXQ5","created_at":"2026-07-05T01:06:09Z"},{"alias_kind":"pith_short_16","alias_value":"424RI2ZSBXQ5H5CR","created_at":"2026-07-05T01:06:09Z"},{"alias_kind":"pith_short_8","alias_value":"424RI2ZS","created_at":"2026-07-05T01:06:09Z"}],"graph_snapshots":[{"event_id":"sha256:061a83f78c98d98c644993ed88ef51b156f29816aa2bb57f18df4211a8c1accd","target":"graph","created_at":"2026-07-05T01:06:09Z","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/1911.09930/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Intrinsic image decomposition, which is an essential task in computer vision, aims to infer the reflectance and shading of the scene. It is challenging since it needs to separate one image into two components. To tackle this, conventional methods introduce various priors to constrain the solution, yet with limited performance. Meanwhile, the problem is typically solved by supervised learning methods, which is actually not an ideal solution since obtaining ground truth reflectance and shading for massive general natural scenes is challenging and even impossible. In this paper, we propose a nove","authors_text":"Feng Lu, Shaodi You, Yu Li, Yunfei Liu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-11-22T09:00:55Z","title":"Unsupervised Learning for Intrinsic Image Decomposition from a Single Image"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1911.09930","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":"sha256:07596cf3541743efd2f6f93acde08c3c15a1c6f6e460c35f438745fbe5851179","target":"record","created_at":"2026-07-05T01:06:09Z","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":"2ae81f57a9fe11d9253e7d0ca782d88c332816e7aef125288843649436c87762","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-11-22T09:00:55Z","title_canon_sha256":"2245209c09ce61da4c1eb56b719a1be1cc8d37a0e62c40dbc499b2319a6c00e6"},"schema_version":"1.0","source":{"id":"1911.09930","kind":"arxiv","version":2}},"canonical_sha256":"e6b9146b320de1d3f4510716b283b1ca47b1c590ac94ac080e774c4952e8de0f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e6b9146b320de1d3f4510716b283b1ca47b1c590ac94ac080e774c4952e8de0f","first_computed_at":"2026-07-05T01:06:09.464521Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:06:09.464521Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ij81WWGej1HwFsz3XP/J6dJIpH0Msx+w+d3Mfb14uaekA7WpyUYTGGsJ/HAODp5CWnQ9jnQ+oGT1/HrIGtfzBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T01:06:09.465093Z","signed_message":"canonical_sha256_bytes"},"source_id":"1911.09930","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:07596cf3541743efd2f6f93acde08c3c15a1c6f6e460c35f438745fbe5851179","sha256:061a83f78c98d98c644993ed88ef51b156f29816aa2bb57f18df4211a8c1accd"],"state_sha256":"eb52c0e00b60f15a0edec7539ebea39b44bb05b12636e80fd2f2ef931aa66225"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WL18nnu8F+YsTaHVBmFpDt2OLEmC5/lfpNN3HhiIOcTnbGIo5QZsjStx6+aAFi23V8hq97Yrx7sqfRegsZSKAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-20T18:46:07.095433Z","bundle_sha256":"9093a8b4ea2d4b051e49843d83cd14b9727d3f8fd37620a6fe343fbf6dd88913"}}