{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:VJHEWJXHCDQYVMVU4OT6ISIEX7","short_pith_number":"pith:VJHEWJXH","canonical_record":{"source":{"id":"1505.07427","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-05-27T18:18:42Z","cross_cats_sorted":["cs.NE","cs.RO"],"title_canon_sha256":"cf2855ffe09914130c8be2e7de464fe113371e97effef07cc8b2dd96492278b7","abstract_canon_sha256":"8a40ea1f36d3e128b3d6cd28c146d1818ec5df818702fbe422ef09a25dd02b3a"},"schema_version":"1.0"},"canonical_sha256":"aa4e4b26e710e18ab2b4e3a7e44904bfc55a0796c13e3c408ff289c97ab7f42f","source":{"kind":"arxiv","id":"1505.07427","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1505.07427","created_at":"2026-05-18T01:20:26Z"},{"alias_kind":"arxiv_version","alias_value":"1505.07427v4","created_at":"2026-05-18T01:20:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1505.07427","created_at":"2026-05-18T01:20:26Z"},{"alias_kind":"pith_short_12","alias_value":"VJHEWJXHCDQY","created_at":"2026-05-18T12:29:44Z"},{"alias_kind":"pith_short_16","alias_value":"VJHEWJXHCDQYVMVU","created_at":"2026-05-18T12:29:44Z"},{"alias_kind":"pith_short_8","alias_value":"VJHEWJXH","created_at":"2026-05-18T12:29:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:VJHEWJXHCDQYVMVU4OT6ISIEX7","target":"record","payload":{"canonical_record":{"source":{"id":"1505.07427","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-05-27T18:18:42Z","cross_cats_sorted":["cs.NE","cs.RO"],"title_canon_sha256":"cf2855ffe09914130c8be2e7de464fe113371e97effef07cc8b2dd96492278b7","abstract_canon_sha256":"8a40ea1f36d3e128b3d6cd28c146d1818ec5df818702fbe422ef09a25dd02b3a"},"schema_version":"1.0"},"canonical_sha256":"aa4e4b26e710e18ab2b4e3a7e44904bfc55a0796c13e3c408ff289c97ab7f42f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:20:26.163631Z","signature_b64":"UzG1rzLhP/lxFk0yMmzIb5BEs127c/kRnE4Fyp80e17xuEwsFWUetqmuzY8Z2U0Whs3gLRapxtagDbyLDFOFCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"aa4e4b26e710e18ab2b4e3a7e44904bfc55a0796c13e3c408ff289c97ab7f42f","last_reissued_at":"2026-05-18T01:20:26.162997Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:20:26.162997Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1505.07427","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:20:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"V2Yy/c8Qin/XNC3ZOloRt6N82Q/c8c3zZWBxVihk3QxUWjlb/LZ0QNrkTMms3A7AOGb1z72jDN60sIJqsukVBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T21:44:35.854162Z"},"content_sha256":"862a166de9433c2fd8a778d293d7095ffa930272bfb8081b78347edb7acb86ae","schema_version":"1.0","event_id":"sha256:862a166de9433c2fd8a778d293d7095ffa930272bfb8081b78347edb7acb86ae"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:VJHEWJXHCDQYVMVU4OT6ISIEX7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NE","cs.RO"],"primary_cat":"cs.CV","authors_text":"Alex Kendall, Matthew Grimes, Roberto Cipolla","submitted_at":"2015-05-27T18:18:42Z","abstract_excerpt":"We present a robust and real-time monocular six degree of freedom relocalization system. Our system trains a convolutional neural network to regress the 6-DOF camera pose from a single RGB image in an end-to-end manner with no need of additional engineering or graph optimisation. The algorithm can operate indoors and outdoors in real time, taking 5ms per frame to compute. It obtains approximately 2m and 6 degree accuracy for large scale outdoor scenes and 0.5m and 10 degree accuracy indoors. This is achieved using an efficient 23 layer deep convnet, demonstrating that convnets can be used to s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1505.07427","kind":"arxiv","version":4},"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":"2026-05-18T01:20:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rA6XzOWgsSiMGwxNfjjSSijgHe7C4cXEjyeG6yBdAN6+dbbXucRqrBUZuNRD+thq2BPfamgQTZDLe9nuZMCdAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T21:44:35.854532Z"},"content_sha256":"dbfc3518af792a374e0b0d24b9fb00ae62acebf0d119aa8d9589faf3efc8cdbc","schema_version":"1.0","event_id":"sha256:dbfc3518af792a374e0b0d24b9fb00ae62acebf0d119aa8d9589faf3efc8cdbc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VJHEWJXHCDQYVMVU4OT6ISIEX7/bundle.json","state_url":"https://pith.science/pith/VJHEWJXHCDQYVMVU4OT6ISIEX7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VJHEWJXHCDQYVMVU4OT6ISIEX7/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":"2026-06-04T21:44:35Z","links":{"resolver":"https://pith.science/pith/VJHEWJXHCDQYVMVU4OT6ISIEX7","bundle":"https://pith.science/pith/VJHEWJXHCDQYVMVU4OT6ISIEX7/bundle.json","state":"https://pith.science/pith/VJHEWJXHCDQYVMVU4OT6ISIEX7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VJHEWJXHCDQYVMVU4OT6ISIEX7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:VJHEWJXHCDQYVMVU4OT6ISIEX7","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":"8a40ea1f36d3e128b3d6cd28c146d1818ec5df818702fbe422ef09a25dd02b3a","cross_cats_sorted":["cs.NE","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-05-27T18:18:42Z","title_canon_sha256":"cf2855ffe09914130c8be2e7de464fe113371e97effef07cc8b2dd96492278b7"},"schema_version":"1.0","source":{"id":"1505.07427","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1505.07427","created_at":"2026-05-18T01:20:26Z"},{"alias_kind":"arxiv_version","alias_value":"1505.07427v4","created_at":"2026-05-18T01:20:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1505.07427","created_at":"2026-05-18T01:20:26Z"},{"alias_kind":"pith_short_12","alias_value":"VJHEWJXHCDQY","created_at":"2026-05-18T12:29:44Z"},{"alias_kind":"pith_short_16","alias_value":"VJHEWJXHCDQYVMVU","created_at":"2026-05-18T12:29:44Z"},{"alias_kind":"pith_short_8","alias_value":"VJHEWJXH","created_at":"2026-05-18T12:29:44Z"}],"graph_snapshots":[{"event_id":"sha256:dbfc3518af792a374e0b0d24b9fb00ae62acebf0d119aa8d9589faf3efc8cdbc","target":"graph","created_at":"2026-05-18T01:20:26Z","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 robust and real-time monocular six degree of freedom relocalization system. Our system trains a convolutional neural network to regress the 6-DOF camera pose from a single RGB image in an end-to-end manner with no need of additional engineering or graph optimisation. The algorithm can operate indoors and outdoors in real time, taking 5ms per frame to compute. It obtains approximately 2m and 6 degree accuracy for large scale outdoor scenes and 0.5m and 10 degree accuracy indoors. This is achieved using an efficient 23 layer deep convnet, demonstrating that convnets can be used to s","authors_text":"Alex Kendall, Matthew Grimes, Roberto Cipolla","cross_cats":["cs.NE","cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-05-27T18:18:42Z","title":"PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1505.07427","kind":"arxiv","version":4},"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":"sha256:862a166de9433c2fd8a778d293d7095ffa930272bfb8081b78347edb7acb86ae","target":"record","created_at":"2026-05-18T01:20:26Z","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":"8a40ea1f36d3e128b3d6cd28c146d1818ec5df818702fbe422ef09a25dd02b3a","cross_cats_sorted":["cs.NE","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-05-27T18:18:42Z","title_canon_sha256":"cf2855ffe09914130c8be2e7de464fe113371e97effef07cc8b2dd96492278b7"},"schema_version":"1.0","source":{"id":"1505.07427","kind":"arxiv","version":4}},"canonical_sha256":"aa4e4b26e710e18ab2b4e3a7e44904bfc55a0796c13e3c408ff289c97ab7f42f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"aa4e4b26e710e18ab2b4e3a7e44904bfc55a0796c13e3c408ff289c97ab7f42f","first_computed_at":"2026-05-18T01:20:26.162997Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:20:26.162997Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UzG1rzLhP/lxFk0yMmzIb5BEs127c/kRnE4Fyp80e17xuEwsFWUetqmuzY8Z2U0Whs3gLRapxtagDbyLDFOFCA==","signature_status":"signed_v1","signed_at":"2026-05-18T01:20:26.163631Z","signed_message":"canonical_sha256_bytes"},"source_id":"1505.07427","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:862a166de9433c2fd8a778d293d7095ffa930272bfb8081b78347edb7acb86ae","sha256:dbfc3518af792a374e0b0d24b9fb00ae62acebf0d119aa8d9589faf3efc8cdbc"],"state_sha256":"7d2dc8ba05de5868c339b18ccf31402feb8367e0665086cff4b8ea1708f249f6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Yewi6AC7L8/J6wRDzEmOeDtTm+XbrJMM7d9uZMm5vDMhw+GgBn+7U8TPmQ2Ov9ZUw6wl5tCW0wLSpuneS+d2Dg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-04T21:44:35.856572Z","bundle_sha256":"5ee57edeb25bec248a3934823a97722e5fd1cfce8f497072c8fe5d84c6410d1f"}}