{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:OJC5TPVJ63HYXCGZVIAHZLRJIN","short_pith_number":"pith:OJC5TPVJ","canonical_record":{"source":{"id":"1903.11633","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-03-27T18:14:50Z","cross_cats_sorted":[],"title_canon_sha256":"e7dbeb1bfa6f9b3f05af0a170c14e5fbe46de480ebe1fdcd021e35b5b9f4541e","abstract_canon_sha256":"bcee60a321d8fe9496203fc289bda8df56a91d3cd9d84ce19cc7aea462444ea2"},"schema_version":"1.0"},"canonical_sha256":"7245d9bea9f6cf8b88d9aa007cae2943456a364f602e4af8ec27935de51a6f79","source":{"kind":"arxiv","id":"1903.11633","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.11633","created_at":"2026-07-04T23:56:48Z"},{"alias_kind":"arxiv_version","alias_value":"1903.11633v2","created_at":"2026-07-04T23:56:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.11633","created_at":"2026-07-04T23:56:48Z"},{"alias_kind":"pith_short_12","alias_value":"OJC5TPVJ63HY","created_at":"2026-07-04T23:56:48Z"},{"alias_kind":"pith_short_16","alias_value":"OJC5TPVJ63HYXCGZ","created_at":"2026-07-04T23:56:48Z"},{"alias_kind":"pith_short_8","alias_value":"OJC5TPVJ","created_at":"2026-07-04T23:56:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:OJC5TPVJ63HYXCGZVIAHZLRJIN","target":"record","payload":{"canonical_record":{"source":{"id":"1903.11633","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-03-27T18:14:50Z","cross_cats_sorted":[],"title_canon_sha256":"e7dbeb1bfa6f9b3f05af0a170c14e5fbe46de480ebe1fdcd021e35b5b9f4541e","abstract_canon_sha256":"bcee60a321d8fe9496203fc289bda8df56a91d3cd9d84ce19cc7aea462444ea2"},"schema_version":"1.0"},"canonical_sha256":"7245d9bea9f6cf8b88d9aa007cae2943456a364f602e4af8ec27935de51a6f79","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-04T23:56:48.042257Z","signature_b64":"OBUGX5qPvjDu8Jo4ufsYiOI1gdjesYxjD8C9DS1I622CVcenUmvYa9YtCWYoqjcZbyalJ1Y2y4N/UuzFqxecCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7245d9bea9f6cf8b88d9aa007cae2943456a364f602e4af8ec27935de51a6f79","last_reissued_at":"2026-07-04T23:56:48.041785Z","signature_status":"signed_v1","first_computed_at":"2026-07-04T23:56:48.041785Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1903.11633","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":"2026-07-04T23:56:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"03Jx7IxgnlaAqMzBMd7GU66KEUTPYLBGv0xBfnL0lRl58XkcO95Ko1IiTNIxyaOVkDnchmQ/yWthFA2Oh/BcBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T21:51:17.020300Z"},"content_sha256":"1a1596bcb77d31c37123ecfec344a68560f4d4342f07ca6c2333fb70c59bf1dd","schema_version":"1.0","event_id":"sha256:1a1596bcb77d31c37123ecfec344a68560f4d4342f07ca6c2333fb70c59bf1dd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:OJC5TPVJ63HYXCGZVIAHZLRJIN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Laplace Landmark Localization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"and Sergey Tulyakov, Joseph P Robinson, Ning Zhang, Yuncheng Li, Yun Fu","submitted_at":"2019-03-27T18:14:50Z","abstract_excerpt":"Landmark localization in images and videos is a classic problem solved in various ways. Nowadays, with deep networks prevailing throughout machine learning, there are revamped interests in pushing facial landmark detection technologies to handle more challenging data. Most efforts use network objectives based on L1 or L2 norms, which have several disadvantages. First of all, the locations of landmarks are determined from generated heatmaps (i.e., confidence maps) from which predicted landmark locations (i.e., the means) get penalized without accounting for the spread: a high scatter correspond"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.11633","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/1903.11633/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":"2026-07-04T23:56:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ukA9uLYmxL6LxLls3o9YeYspDeXO60Rp1aPcJT+omAAl3dvduifNWzX6jj0HMmoGTT/IB4fDcRBp+EBYGWQ+CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T21:51:17.021122Z"},"content_sha256":"2dc84d5f17443fa21ffc22d9c10ee4a8c381d82d7fb5a563e23ee766d426e91c","schema_version":"1.0","event_id":"sha256:2dc84d5f17443fa21ffc22d9c10ee4a8c381d82d7fb5a563e23ee766d426e91c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OJC5TPVJ63HYXCGZVIAHZLRJIN/bundle.json","state_url":"https://pith.science/pith/OJC5TPVJ63HYXCGZVIAHZLRJIN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OJC5TPVJ63HYXCGZVIAHZLRJIN/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":"2026-08-20T21:51:17Z","links":{"resolver":"https://pith.science/pith/OJC5TPVJ63HYXCGZVIAHZLRJIN","bundle":"https://pith.science/pith/OJC5TPVJ63HYXCGZVIAHZLRJIN/bundle.json","state":"https://pith.science/pith/OJC5TPVJ63HYXCGZVIAHZLRJIN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OJC5TPVJ63HYXCGZVIAHZLRJIN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:OJC5TPVJ63HYXCGZVIAHZLRJIN","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":"bcee60a321d8fe9496203fc289bda8df56a91d3cd9d84ce19cc7aea462444ea2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-03-27T18:14:50Z","title_canon_sha256":"e7dbeb1bfa6f9b3f05af0a170c14e5fbe46de480ebe1fdcd021e35b5b9f4541e"},"schema_version":"1.0","source":{"id":"1903.11633","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.11633","created_at":"2026-07-04T23:56:48Z"},{"alias_kind":"arxiv_version","alias_value":"1903.11633v2","created_at":"2026-07-04T23:56:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.11633","created_at":"2026-07-04T23:56:48Z"},{"alias_kind":"pith_short_12","alias_value":"OJC5TPVJ63HY","created_at":"2026-07-04T23:56:48Z"},{"alias_kind":"pith_short_16","alias_value":"OJC5TPVJ63HYXCGZ","created_at":"2026-07-04T23:56:48Z"},{"alias_kind":"pith_short_8","alias_value":"OJC5TPVJ","created_at":"2026-07-04T23:56:48Z"}],"graph_snapshots":[{"event_id":"sha256:2dc84d5f17443fa21ffc22d9c10ee4a8c381d82d7fb5a563e23ee766d426e91c","target":"graph","created_at":"2026-07-04T23:56:48Z","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/1903.11633/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Landmark localization in images and videos is a classic problem solved in various ways. Nowadays, with deep networks prevailing throughout machine learning, there are revamped interests in pushing facial landmark detection technologies to handle more challenging data. Most efforts use network objectives based on L1 or L2 norms, which have several disadvantages. First of all, the locations of landmarks are determined from generated heatmaps (i.e., confidence maps) from which predicted landmark locations (i.e., the means) get penalized without accounting for the spread: a high scatter correspond","authors_text":"and Sergey Tulyakov, Joseph P Robinson, Ning Zhang, Yuncheng Li, Yun Fu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-03-27T18:14:50Z","title":"Laplace Landmark Localization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.11633","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":"sha256:1a1596bcb77d31c37123ecfec344a68560f4d4342f07ca6c2333fb70c59bf1dd","target":"record","created_at":"2026-07-04T23:56:48Z","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":"bcee60a321d8fe9496203fc289bda8df56a91d3cd9d84ce19cc7aea462444ea2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-03-27T18:14:50Z","title_canon_sha256":"e7dbeb1bfa6f9b3f05af0a170c14e5fbe46de480ebe1fdcd021e35b5b9f4541e"},"schema_version":"1.0","source":{"id":"1903.11633","kind":"arxiv","version":2}},"canonical_sha256":"7245d9bea9f6cf8b88d9aa007cae2943456a364f602e4af8ec27935de51a6f79","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7245d9bea9f6cf8b88d9aa007cae2943456a364f602e4af8ec27935de51a6f79","first_computed_at":"2026-07-04T23:56:48.041785Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-04T23:56:48.041785Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"OBUGX5qPvjDu8Jo4ufsYiOI1gdjesYxjD8C9DS1I622CVcenUmvYa9YtCWYoqjcZbyalJ1Y2y4N/UuzFqxecCg==","signature_status":"signed_v1","signed_at":"2026-07-04T23:56:48.042257Z","signed_message":"canonical_sha256_bytes"},"source_id":"1903.11633","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1a1596bcb77d31c37123ecfec344a68560f4d4342f07ca6c2333fb70c59bf1dd","sha256:2dc84d5f17443fa21ffc22d9c10ee4a8c381d82d7fb5a563e23ee766d426e91c"],"state_sha256":"39341fa4df85c838ac88b8814042026c070b0384cac51d0ab0a9ad1de3100238"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kGqJ+zmZBh1U0l3UekEG3VWFIhw/5bextYWEnBTQGVqpecjEkeDwP7QhDFSCFssDCkIc2XiDFa+7zuCu53mMDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T21:51:17.026258Z","bundle_sha256":"48f2b2d303225bf5d31f609fafcc22a8832a8cd8e4744d44c2acf9b08a443d4c"}}