{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:IMBBTK2EKVJGZ2NIS7CNMJG4ZA","short_pith_number":"pith:IMBBTK2E","canonical_record":{"source":{"id":"1511.04031","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-11-12T19:50:53Z","cross_cats_sorted":[],"title_canon_sha256":"6cbf9d0422ee38354b07e43fe353602464a4baaf45c6b53c8d12f1b2c998f65f","abstract_canon_sha256":"9cbbc70db8de22013337b9ee966d971e89acf669d0ba843565f1d127d6f340ff"},"schema_version":"1.0"},"canonical_sha256":"430219ab4455526ce9a897c4d624dcc808a9971909f6f7bbd33d2faaa3d0bc70","source":{"kind":"arxiv","id":"1511.04031","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1511.04031","created_at":"2026-05-18T01:18:41Z"},{"alias_kind":"arxiv_version","alias_value":"1511.04031v2","created_at":"2026-05-18T01:18:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1511.04031","created_at":"2026-05-18T01:18:41Z"},{"alias_kind":"pith_short_12","alias_value":"IMBBTK2EKVJG","created_at":"2026-05-18T12:29:25Z"},{"alias_kind":"pith_short_16","alias_value":"IMBBTK2EKVJGZ2NI","created_at":"2026-05-18T12:29:25Z"},{"alias_kind":"pith_short_8","alias_value":"IMBBTK2E","created_at":"2026-05-18T12:29:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:IMBBTK2EKVJGZ2NIS7CNMJG4ZA","target":"record","payload":{"canonical_record":{"source":{"id":"1511.04031","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-11-12T19:50:53Z","cross_cats_sorted":[],"title_canon_sha256":"6cbf9d0422ee38354b07e43fe353602464a4baaf45c6b53c8d12f1b2c998f65f","abstract_canon_sha256":"9cbbc70db8de22013337b9ee966d971e89acf669d0ba843565f1d127d6f340ff"},"schema_version":"1.0"},"canonical_sha256":"430219ab4455526ce9a897c4d624dcc808a9971909f6f7bbd33d2faaa3d0bc70","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:18:41.554555Z","signature_b64":"sZzoRSoYZVxK4t7fv4jlAtOoTAy0w4MTH54QyrFEMbgDbws92Iqiy+NktZZCJ3UNat8HAWdgkb1K/L7jA5CaAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"430219ab4455526ce9a897c4d624dcc808a9971909f6f7bbd33d2faaa3d0bc70","last_reissued_at":"2026-05-18T01:18:41.553988Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:18:41.553988Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1511.04031","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":"2026-05-18T01:18:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dR28FzDOhirpQZWT7B36TDLwjZzpznv7pwYpcIvLkCQRhAYWhNf1tcfN5NZD3UJNOFK7pixfO8/8AZGf1KDXAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T12:25:46.962236Z"},"content_sha256":"fe367b5f1cbeab625fab6c6ac3976ebd1adf984de0f80bd1a4e9c9b050811215","schema_version":"1.0","event_id":"sha256:fe367b5f1cbeab625fab6c6ac3976ebd1adf984de0f80bd1a4e9c9b050811215"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:IMBBTK2EKVJGZ2NIS7CNMJG4ZA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Facial Landmark Detection with Tweaked Convolutional Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Gerard Medioni, KangGeon Kim, Prem Natarajan, Tal Hassner, Yue Wu","submitted_at":"2015-11-12T19:50:53Z","abstract_excerpt":"We present a novel convolutional neural network (CNN) design for facial landmark coordinate regression. We examine the intermediate features of a standard CNN trained for landmark detection and show that features extracted from later, more specialized layers capture rough landmark locations. This provides a natural means of applying differential treatment midway through the network, tweaking processing based on facial alignment. The resulting Tweaked CNN model (TCNN) harnesses the robustness of CNNs for landmark detection, in an appearance-sensitive manner without training multi-part or multi-"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1511.04031","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":"2026-05-18T01:18:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"w+TNR7P68HM7AWfkjka2cFHdehrrrdJNuAcs4DuYFBHxqr7bzJu8dgtGSyU0PR2CyYIf+V9wrOI8iK+AOLn1Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T12:25:46.962611Z"},"content_sha256":"b206ca2852a07b26de64f75d6d389010df71ae06be2771eea02e4ca4c1d3caeb","schema_version":"1.0","event_id":"sha256:b206ca2852a07b26de64f75d6d389010df71ae06be2771eea02e4ca4c1d3caeb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IMBBTK2EKVJGZ2NIS7CNMJG4ZA/bundle.json","state_url":"https://pith.science/pith/IMBBTK2EKVJGZ2NIS7CNMJG4ZA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IMBBTK2EKVJGZ2NIS7CNMJG4ZA/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":"2026-05-26T12:25:46Z","links":{"resolver":"https://pith.science/pith/IMBBTK2EKVJGZ2NIS7CNMJG4ZA","bundle":"https://pith.science/pith/IMBBTK2EKVJGZ2NIS7CNMJG4ZA/bundle.json","state":"https://pith.science/pith/IMBBTK2EKVJGZ2NIS7CNMJG4ZA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IMBBTK2EKVJGZ2NIS7CNMJG4ZA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:IMBBTK2EKVJGZ2NIS7CNMJG4ZA","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":"9cbbc70db8de22013337b9ee966d971e89acf669d0ba843565f1d127d6f340ff","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-11-12T19:50:53Z","title_canon_sha256":"6cbf9d0422ee38354b07e43fe353602464a4baaf45c6b53c8d12f1b2c998f65f"},"schema_version":"1.0","source":{"id":"1511.04031","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1511.04031","created_at":"2026-05-18T01:18:41Z"},{"alias_kind":"arxiv_version","alias_value":"1511.04031v2","created_at":"2026-05-18T01:18:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1511.04031","created_at":"2026-05-18T01:18:41Z"},{"alias_kind":"pith_short_12","alias_value":"IMBBTK2EKVJG","created_at":"2026-05-18T12:29:25Z"},{"alias_kind":"pith_short_16","alias_value":"IMBBTK2EKVJGZ2NI","created_at":"2026-05-18T12:29:25Z"},{"alias_kind":"pith_short_8","alias_value":"IMBBTK2E","created_at":"2026-05-18T12:29:25Z"}],"graph_snapshots":[{"event_id":"sha256:b206ca2852a07b26de64f75d6d389010df71ae06be2771eea02e4ca4c1d3caeb","target":"graph","created_at":"2026-05-18T01:18:41Z","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":"We present a novel convolutional neural network (CNN) design for facial landmark coordinate regression. We examine the intermediate features of a standard CNN trained for landmark detection and show that features extracted from later, more specialized layers capture rough landmark locations. This provides a natural means of applying differential treatment midway through the network, tweaking processing based on facial alignment. The resulting Tweaked CNN model (TCNN) harnesses the robustness of CNNs for landmark detection, in an appearance-sensitive manner without training multi-part or multi-","authors_text":"Gerard Medioni, KangGeon Kim, Prem Natarajan, Tal Hassner, Yue Wu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-11-12T19:50:53Z","title":"Facial Landmark Detection with Tweaked Convolutional Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1511.04031","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:fe367b5f1cbeab625fab6c6ac3976ebd1adf984de0f80bd1a4e9c9b050811215","target":"record","created_at":"2026-05-18T01:18:41Z","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":"9cbbc70db8de22013337b9ee966d971e89acf669d0ba843565f1d127d6f340ff","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-11-12T19:50:53Z","title_canon_sha256":"6cbf9d0422ee38354b07e43fe353602464a4baaf45c6b53c8d12f1b2c998f65f"},"schema_version":"1.0","source":{"id":"1511.04031","kind":"arxiv","version":2}},"canonical_sha256":"430219ab4455526ce9a897c4d624dcc808a9971909f6f7bbd33d2faaa3d0bc70","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"430219ab4455526ce9a897c4d624dcc808a9971909f6f7bbd33d2faaa3d0bc70","first_computed_at":"2026-05-18T01:18:41.553988Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:18:41.553988Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"sZzoRSoYZVxK4t7fv4jlAtOoTAy0w4MTH54QyrFEMbgDbws92Iqiy+NktZZCJ3UNat8HAWdgkb1K/L7jA5CaAg==","signature_status":"signed_v1","signed_at":"2026-05-18T01:18:41.554555Z","signed_message":"canonical_sha256_bytes"},"source_id":"1511.04031","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fe367b5f1cbeab625fab6c6ac3976ebd1adf984de0f80bd1a4e9c9b050811215","sha256:b206ca2852a07b26de64f75d6d389010df71ae06be2771eea02e4ca4c1d3caeb"],"state_sha256":"1051badc5587ccea31f79583d276425584f90a53b06b1524eb983b3c6291a98c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tWL13GvlRdSS5SHeBSi7ATVzjpavNfKOW0KA3e7CsltctZTdK36vOhwHqAECb3KX8BOznxPFzU9Kc3dceG11Dg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T12:25:46.965190Z","bundle_sha256":"3446fc012e0f79562d28d69462755fd75885492129aead63170d16b714cdc9d6"}}