{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:EWSEP54HJAL52MBDW6HCBUHCDE","short_pith_number":"pith:EWSEP54H","canonical_record":{"source":{"id":"1912.04384","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-12-09T21:28:50Z","cross_cats_sorted":[],"title_canon_sha256":"5aa9e4b644f3d2f614bba573dfa3afb7be03ccc27f223dbb4f3f0130e5a98342","abstract_canon_sha256":"37707835608ccc444a03b6da722d4d5d7425e8654d09ab00d7c0c2e1e267e618"},"schema_version":"1.0"},"canonical_sha256":"25a447f7874817dd3023b78e20d0e2191315c3da628fd1d2584cae9545d53459","source":{"kind":"arxiv","id":"1912.04384","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1912.04384","created_at":"2026-07-05T00:24:58Z"},{"alias_kind":"arxiv_version","alias_value":"1912.04384v1","created_at":"2026-07-05T00:24:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1912.04384","created_at":"2026-07-05T00:24:58Z"},{"alias_kind":"pith_short_12","alias_value":"EWSEP54HJAL5","created_at":"2026-07-05T00:24:58Z"},{"alias_kind":"pith_short_16","alias_value":"EWSEP54HJAL52MBD","created_at":"2026-07-05T00:24:58Z"},{"alias_kind":"pith_short_8","alias_value":"EWSEP54H","created_at":"2026-07-05T00:24:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:EWSEP54HJAL52MBDW6HCBUHCDE","target":"record","payload":{"canonical_record":{"source":{"id":"1912.04384","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-12-09T21:28:50Z","cross_cats_sorted":[],"title_canon_sha256":"5aa9e4b644f3d2f614bba573dfa3afb7be03ccc27f223dbb4f3f0130e5a98342","abstract_canon_sha256":"37707835608ccc444a03b6da722d4d5d7425e8654d09ab00d7c0c2e1e267e618"},"schema_version":"1.0"},"canonical_sha256":"25a447f7874817dd3023b78e20d0e2191315c3da628fd1d2584cae9545d53459","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:24:58.725643Z","signature_b64":"opS89hvwlPtzmRc4nCtMDkeV/umyezzSUVWqORairqkxWRV3L0XQUOAeSPXdixYKM1OWy8efFNOcw39hNFaFCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"25a447f7874817dd3023b78e20d0e2191315c3da628fd1d2584cae9545d53459","last_reissued_at":"2026-07-05T00:24:58.725165Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:24:58.725165Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1912.04384","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":"2026-07-05T00:24:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jRkqZMU6Cf2VQeX7Vyve1jwGoGVTm09gp0P1tMeZvlHsa9jv9hDg12sadRudqobinH5K+igpK++kFal4R+JbBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T03:30:29.323922Z"},"content_sha256":"ee5289a9154d88de54043fd175b3189a04128ea2da4968dc9e43ccaab49d492f","schema_version":"1.0","event_id":"sha256:ee5289a9154d88de54043fd175b3189a04128ea2da4968dc9e43ccaab49d492f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:EWSEP54HJAL52MBDW6HCBUHCDE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Training Deep Neural Networks to Detect Repeatable 2D Features Using Large Amounts of 3D World Capture Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Alexander Mai, Allen Yang, Joseph Menke","submitted_at":"2019-12-09T21:28:50Z","abstract_excerpt":"Image space feature detection is the act of selecting points or parts of an image that are easy to distinguish from the surrounding image region. By combining a repeatable point detection with a descriptor, parts of an image can be matched with one another, which is useful in applications like estimating pose from camera input or rectifying images. Recently, precise indoor tracking has started to become important for Augmented and Virtual reality as it is necessary to allow positioning of a headset in 3D space without the need for external tracking devices. Several modern feature detectors use"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1912.04384","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/1912.04384/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":"2026-07-05T00:24:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Y6EB8SbSWn4eHagYrNKKzfov/xg0qQ/evIuLo52pCCAyPsLQR6c+BO+2kzdyU6xOUFxqbUIdgoN/zMrOe93eAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T03:30:29.324294Z"},"content_sha256":"5d46c99f4778b6d7451e74e907e3bebc629f2f2bca64d92aec83a070d0c6ebcb","schema_version":"1.0","event_id":"sha256:5d46c99f4778b6d7451e74e907e3bebc629f2f2bca64d92aec83a070d0c6ebcb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EWSEP54HJAL52MBDW6HCBUHCDE/bundle.json","state_url":"https://pith.science/pith/EWSEP54HJAL52MBDW6HCBUHCDE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EWSEP54HJAL52MBDW6HCBUHCDE/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":"2026-07-09T03:30:29Z","links":{"resolver":"https://pith.science/pith/EWSEP54HJAL52MBDW6HCBUHCDE","bundle":"https://pith.science/pith/EWSEP54HJAL52MBDW6HCBUHCDE/bundle.json","state":"https://pith.science/pith/EWSEP54HJAL52MBDW6HCBUHCDE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EWSEP54HJAL52MBDW6HCBUHCDE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:EWSEP54HJAL52MBDW6HCBUHCDE","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":"37707835608ccc444a03b6da722d4d5d7425e8654d09ab00d7c0c2e1e267e618","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-12-09T21:28:50Z","title_canon_sha256":"5aa9e4b644f3d2f614bba573dfa3afb7be03ccc27f223dbb4f3f0130e5a98342"},"schema_version":"1.0","source":{"id":"1912.04384","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1912.04384","created_at":"2026-07-05T00:24:58Z"},{"alias_kind":"arxiv_version","alias_value":"1912.04384v1","created_at":"2026-07-05T00:24:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1912.04384","created_at":"2026-07-05T00:24:58Z"},{"alias_kind":"pith_short_12","alias_value":"EWSEP54HJAL5","created_at":"2026-07-05T00:24:58Z"},{"alias_kind":"pith_short_16","alias_value":"EWSEP54HJAL52MBD","created_at":"2026-07-05T00:24:58Z"},{"alias_kind":"pith_short_8","alias_value":"EWSEP54H","created_at":"2026-07-05T00:24:58Z"}],"graph_snapshots":[{"event_id":"sha256:5d46c99f4778b6d7451e74e907e3bebc629f2f2bca64d92aec83a070d0c6ebcb","target":"graph","created_at":"2026-07-05T00:24:58Z","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/1912.04384/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Image space feature detection is the act of selecting points or parts of an image that are easy to distinguish from the surrounding image region. By combining a repeatable point detection with a descriptor, parts of an image can be matched with one another, which is useful in applications like estimating pose from camera input or rectifying images. Recently, precise indoor tracking has started to become important for Augmented and Virtual reality as it is necessary to allow positioning of a headset in 3D space without the need for external tracking devices. Several modern feature detectors use","authors_text":"Alexander Mai, Allen Yang, Joseph Menke","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-12-09T21:28:50Z","title":"Training Deep Neural Networks to Detect Repeatable 2D Features Using Large Amounts of 3D World Capture Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1912.04384","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:ee5289a9154d88de54043fd175b3189a04128ea2da4968dc9e43ccaab49d492f","target":"record","created_at":"2026-07-05T00:24:58Z","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":"37707835608ccc444a03b6da722d4d5d7425e8654d09ab00d7c0c2e1e267e618","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-12-09T21:28:50Z","title_canon_sha256":"5aa9e4b644f3d2f614bba573dfa3afb7be03ccc27f223dbb4f3f0130e5a98342"},"schema_version":"1.0","source":{"id":"1912.04384","kind":"arxiv","version":1}},"canonical_sha256":"25a447f7874817dd3023b78e20d0e2191315c3da628fd1d2584cae9545d53459","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"25a447f7874817dd3023b78e20d0e2191315c3da628fd1d2584cae9545d53459","first_computed_at":"2026-07-05T00:24:58.725165Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:24:58.725165Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"opS89hvwlPtzmRc4nCtMDkeV/umyezzSUVWqORairqkxWRV3L0XQUOAeSPXdixYKM1OWy8efFNOcw39hNFaFCw==","signature_status":"signed_v1","signed_at":"2026-07-05T00:24:58.725643Z","signed_message":"canonical_sha256_bytes"},"source_id":"1912.04384","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ee5289a9154d88de54043fd175b3189a04128ea2da4968dc9e43ccaab49d492f","sha256:5d46c99f4778b6d7451e74e907e3bebc629f2f2bca64d92aec83a070d0c6ebcb"],"state_sha256":"d594d64c53b06f48204b3b6a2f67313f6b33e7483acb1b624db8d7bcf2231c1c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VgAZhjFdJI0jPPy0IJ/ba9wmQNpSXTO+lQLnPPE8jQEQSgC76EZa6h6ZpgAa3H9vEskl+t+JfVGvMiWBi5vvCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-09T03:30:29.326459Z","bundle_sha256":"c6c129e0772f6ec03ee677098fa3e0a4d0264df7b5f8c2d8fdc5569a736abc40"}}