{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:I6BA2BGPYEATAZ2HOOV37YCCXC","short_pith_number":"pith:I6BA2BGP","canonical_record":{"source":{"id":"1808.07572","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2018-08-22T21:48:58Z","cross_cats_sorted":[],"title_canon_sha256":"437ea3575836ab1a976b836a5cf21624db48bbfffd7b80c35bea309c8c5d01ff","abstract_canon_sha256":"caf6a1bbcad6889e109421b5274cdb1ab6dbcc6d280d3c939d3a1d08e783a3ee"},"schema_version":"1.0"},"canonical_sha256":"47820d04cfc10130674773abbfe042b88fd1512087b7a5fc899efaf8c383aebe","source":{"kind":"arxiv","id":"1808.07572","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.07572","created_at":"2026-05-18T00:07:26Z"},{"alias_kind":"arxiv_version","alias_value":"1808.07572v1","created_at":"2026-05-18T00:07:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.07572","created_at":"2026-05-18T00:07:26Z"},{"alias_kind":"pith_short_12","alias_value":"I6BA2BGPYEAT","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"I6BA2BGPYEATAZ2H","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"I6BA2BGP","created_at":"2026-05-18T12:32:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:I6BA2BGPYEATAZ2HOOV37YCCXC","target":"record","payload":{"canonical_record":{"source":{"id":"1808.07572","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2018-08-22T21:48:58Z","cross_cats_sorted":[],"title_canon_sha256":"437ea3575836ab1a976b836a5cf21624db48bbfffd7b80c35bea309c8c5d01ff","abstract_canon_sha256":"caf6a1bbcad6889e109421b5274cdb1ab6dbcc6d280d3c939d3a1d08e783a3ee"},"schema_version":"1.0"},"canonical_sha256":"47820d04cfc10130674773abbfe042b88fd1512087b7a5fc899efaf8c383aebe","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:07:26.899621Z","signature_b64":"5R5a4fAkEhEWklKTEN8+zseBa/7fEReygAdckAVZF6vJ3G3IIoGkcadNUbdp1bHqXCb15p3riU/IlpGi6Bt4Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"47820d04cfc10130674773abbfe042b88fd1512087b7a5fc899efaf8c383aebe","last_reissued_at":"2026-05-18T00:07:26.898955Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:07:26.898955Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1808.07572","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":"2026-05-18T00:07:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"877/c8+DiIURrV6dr1OeB2SEnbEcxmg2d5E/wpgcNnY7lan7vzcKhM//G5AqFzEn5alyL7D1Z5cOgbztMvpUBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T05:05:58.401330Z"},"content_sha256":"6e72cb14982dde68a9fcd86edfc371e3f4c5b66e2e26483b5a951093376bdca6","schema_version":"1.0","event_id":"sha256:6e72cb14982dde68a9fcd86edfc371e3f4c5b66e2e26483b5a951093376bdca6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:I6BA2BGPYEATAZ2HOOV37YCCXC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Towards A Deep Insight into Landmark-based Visual Place Recognition: Methodology and Practice","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Bo Yang, Hong Zhang, Jun Li, Xiaosu Xu","submitted_at":"2018-08-22T21:48:58Z","abstract_excerpt":"In this paper, we address the problem of landmark-based visual place recognition. In the state-of-the-art method, accurate object proposal algorithms are first leveraged for generating a set of local regions containing particular landmarks with high confidence. Then, these candidate regions are represented by deep features and pairwise matching is performed in an exhaustive manner for the similarity measure. Despite its success, conventional object proposal methods usually produce massive landmark-dependent image patches exhibiting significant distribution variance in scale and overlap. As a r"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.07572","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":""},"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":"2026-05-18T00:07:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Di/pawijMrbzkX8ywAuoyddJFTSTuK9zp84keuzFERJBlVRoz7YrU6bpXI8Txh3KdH8ALMMTWq7BQJgkssevDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T05:05:58.401674Z"},"content_sha256":"322eb46d36dcfb8e48e1961b3a2cbb01660fdd8f47c18c4421bd540d68cd7ff7","schema_version":"1.0","event_id":"sha256:322eb46d36dcfb8e48e1961b3a2cbb01660fdd8f47c18c4421bd540d68cd7ff7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/I6BA2BGPYEATAZ2HOOV37YCCXC/bundle.json","state_url":"https://pith.science/pith/I6BA2BGPYEATAZ2HOOV37YCCXC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/I6BA2BGPYEATAZ2HOOV37YCCXC/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":"2026-06-04T05:05:58Z","links":{"resolver":"https://pith.science/pith/I6BA2BGPYEATAZ2HOOV37YCCXC","bundle":"https://pith.science/pith/I6BA2BGPYEATAZ2HOOV37YCCXC/bundle.json","state":"https://pith.science/pith/I6BA2BGPYEATAZ2HOOV37YCCXC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/I6BA2BGPYEATAZ2HOOV37YCCXC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:I6BA2BGPYEATAZ2HOOV37YCCXC","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":"caf6a1bbcad6889e109421b5274cdb1ab6dbcc6d280d3c939d3a1d08e783a3ee","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2018-08-22T21:48:58Z","title_canon_sha256":"437ea3575836ab1a976b836a5cf21624db48bbfffd7b80c35bea309c8c5d01ff"},"schema_version":"1.0","source":{"id":"1808.07572","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.07572","created_at":"2026-05-18T00:07:26Z"},{"alias_kind":"arxiv_version","alias_value":"1808.07572v1","created_at":"2026-05-18T00:07:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.07572","created_at":"2026-05-18T00:07:26Z"},{"alias_kind":"pith_short_12","alias_value":"I6BA2BGPYEAT","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"I6BA2BGPYEATAZ2H","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"I6BA2BGP","created_at":"2026-05-18T12:32:28Z"}],"graph_snapshots":[{"event_id":"sha256:322eb46d36dcfb8e48e1961b3a2cbb01660fdd8f47c18c4421bd540d68cd7ff7","target":"graph","created_at":"2026-05-18T00:07:26Z","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":"In this paper, we address the problem of landmark-based visual place recognition. In the state-of-the-art method, accurate object proposal algorithms are first leveraged for generating a set of local regions containing particular landmarks with high confidence. Then, these candidate regions are represented by deep features and pairwise matching is performed in an exhaustive manner for the similarity measure. Despite its success, conventional object proposal methods usually produce massive landmark-dependent image patches exhibiting significant distribution variance in scale and overlap. As a r","authors_text":"Bo Yang, Hong Zhang, Jun Li, Xiaosu Xu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2018-08-22T21:48:58Z","title":"Towards A Deep Insight into Landmark-based Visual Place Recognition: Methodology and Practice"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.07572","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":"sha256:6e72cb14982dde68a9fcd86edfc371e3f4c5b66e2e26483b5a951093376bdca6","target":"record","created_at":"2026-05-18T00:07:26Z","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":"caf6a1bbcad6889e109421b5274cdb1ab6dbcc6d280d3c939d3a1d08e783a3ee","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2018-08-22T21:48:58Z","title_canon_sha256":"437ea3575836ab1a976b836a5cf21624db48bbfffd7b80c35bea309c8c5d01ff"},"schema_version":"1.0","source":{"id":"1808.07572","kind":"arxiv","version":1}},"canonical_sha256":"47820d04cfc10130674773abbfe042b88fd1512087b7a5fc899efaf8c383aebe","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"47820d04cfc10130674773abbfe042b88fd1512087b7a5fc899efaf8c383aebe","first_computed_at":"2026-05-18T00:07:26.898955Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:07:26.898955Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5R5a4fAkEhEWklKTEN8+zseBa/7fEReygAdckAVZF6vJ3G3IIoGkcadNUbdp1bHqXCb15p3riU/IlpGi6Bt4Aw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:07:26.899621Z","signed_message":"canonical_sha256_bytes"},"source_id":"1808.07572","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6e72cb14982dde68a9fcd86edfc371e3f4c5b66e2e26483b5a951093376bdca6","sha256:322eb46d36dcfb8e48e1961b3a2cbb01660fdd8f47c18c4421bd540d68cd7ff7"],"state_sha256":"af9f936874910b0b1b879f06815b9cf5dbe0219ee3b70c83a6300a0fa8a084d5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ckupZ18MoS/H9O7Es+wl9fqN6PdpgCj8XDHYsA2xBV1ZOcSylaASunyfya7FaktmTX7qdfzfRJa5GDz6D2ROAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-04T05:05:58.403516Z","bundle_sha256":"fa131b154699167e4d22a01f69d56b814a5add0ca0d5a66f1fa6d2edc2e4509b"}}