{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:P4FUFGAXYLYR2Z2RI7ES674FHI","short_pith_number":"pith:P4FUFGAX","canonical_record":{"source":{"id":"1904.01892","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-03T10:11:22Z","cross_cats_sorted":[],"title_canon_sha256":"b3cc2ac93fc74c100d02e9cca8f8b18ba305e9e8795091ee64b8cd0f35f0cb4b","abstract_canon_sha256":"a84d96cb56b6901a8846719a3a392ff4b777805222b5140aa0dd6350d0de23c6"},"schema_version":"1.0"},"canonical_sha256":"7f0b429817c2f11d675147c92f7f853a1aa664534d4daec5343467a374d507c1","source":{"kind":"arxiv","id":"1904.01892","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.01892","created_at":"2026-05-17T23:49:20Z"},{"alias_kind":"arxiv_version","alias_value":"1904.01892v2","created_at":"2026-05-17T23:49:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.01892","created_at":"2026-05-17T23:49:20Z"},{"alias_kind":"pith_short_12","alias_value":"P4FUFGAXYLYR","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_16","alias_value":"P4FUFGAXYLYR2Z2R","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_8","alias_value":"P4FUFGAX","created_at":"2026-05-18T12:33:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:P4FUFGAXYLYR2Z2RI7ES674FHI","target":"record","payload":{"canonical_record":{"source":{"id":"1904.01892","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-03T10:11:22Z","cross_cats_sorted":[],"title_canon_sha256":"b3cc2ac93fc74c100d02e9cca8f8b18ba305e9e8795091ee64b8cd0f35f0cb4b","abstract_canon_sha256":"a84d96cb56b6901a8846719a3a392ff4b777805222b5140aa0dd6350d0de23c6"},"schema_version":"1.0"},"canonical_sha256":"7f0b429817c2f11d675147c92f7f853a1aa664534d4daec5343467a374d507c1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:49:20.038859Z","signature_b64":"+Jlf4Y2ZD6Bh6eJNB+OUaCub9BVaSlDLF36FKreechEp6dqGqYJXPPyJuAJe1l+S+ByOgrq+ngH5i/hJxMBwCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7f0b429817c2f11d675147c92f7f853a1aa664534d4daec5343467a374d507c1","last_reissued_at":"2026-05-17T23:49:20.038181Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:49:20.038181Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1904.01892","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":"2026-05-17T23:49:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PONV3+P5qQ5KAPbBHAevv5XfnX/auM/FpldWnESD9jT7PpVXFamEKoiZGeGpTmKLFjfYI9XV3SG50EjiX759Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T08:29:20.561878Z"},"content_sha256":"df5dfaefbdda0408f6f1838787c91f6acbdf8391c6c2c69aed9cf2358a672ae9","schema_version":"1.0","event_id":"sha256:df5dfaefbdda0408f6f1838787c91f6acbdf8391c6c2c69aed9cf2358a672ae9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:P4FUFGAXYLYR2Z2RI7ES674FHI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Beyond Tracking: Selecting Memory and Refining Poses for Deep Visual Odometry","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Fei Xue, Hongbin Zha, Junqiu Wang, Qiuyuan Wang, Shunkai Li, Xin Wang","submitted_at":"2019-04-03T10:11:22Z","abstract_excerpt":"Most previous learning-based visual odometry (VO) methods take VO as a pure tracking problem. In contrast, we present a VO framework by incorporating two additional components called Memory and Refining. The Memory component preserves global information by employing an adaptive and efficient selection strategy. The Refining component ameliorates previous results with the contexts stored in the Memory by adopting a spatial-temporal attention mechanism for feature distilling. Experiments on the KITTI and TUM-RGBD benchmark datasets demonstrate that our method outperforms state-of-the-art learnin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.01892","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":"2026-05-17T23:49:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oAI71sojZ3yGEtx44CbXyPRDKJHGNbVA+Cm3fd07rOtUWbLW6mBj63deX3jE5HSeHNzfFO7j0/MXtDexDzMrCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T08:29:20.562226Z"},"content_sha256":"ec4044c94a0312cdfbab49ab5cc2a0fa8907dbef2fa38690e4a42ce11bc050c0","schema_version":"1.0","event_id":"sha256:ec4044c94a0312cdfbab49ab5cc2a0fa8907dbef2fa38690e4a42ce11bc050c0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/P4FUFGAXYLYR2Z2RI7ES674FHI/bundle.json","state_url":"https://pith.science/pith/P4FUFGAXYLYR2Z2RI7ES674FHI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/P4FUFGAXYLYR2Z2RI7ES674FHI/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":"2026-06-05T08:29:20Z","links":{"resolver":"https://pith.science/pith/P4FUFGAXYLYR2Z2RI7ES674FHI","bundle":"https://pith.science/pith/P4FUFGAXYLYR2Z2RI7ES674FHI/bundle.json","state":"https://pith.science/pith/P4FUFGAXYLYR2Z2RI7ES674FHI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/P4FUFGAXYLYR2Z2RI7ES674FHI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:P4FUFGAXYLYR2Z2RI7ES674FHI","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":"a84d96cb56b6901a8846719a3a392ff4b777805222b5140aa0dd6350d0de23c6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-03T10:11:22Z","title_canon_sha256":"b3cc2ac93fc74c100d02e9cca8f8b18ba305e9e8795091ee64b8cd0f35f0cb4b"},"schema_version":"1.0","source":{"id":"1904.01892","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.01892","created_at":"2026-05-17T23:49:20Z"},{"alias_kind":"arxiv_version","alias_value":"1904.01892v2","created_at":"2026-05-17T23:49:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.01892","created_at":"2026-05-17T23:49:20Z"},{"alias_kind":"pith_short_12","alias_value":"P4FUFGAXYLYR","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_16","alias_value":"P4FUFGAXYLYR2Z2R","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_8","alias_value":"P4FUFGAX","created_at":"2026-05-18T12:33:24Z"}],"graph_snapshots":[{"event_id":"sha256:ec4044c94a0312cdfbab49ab5cc2a0fa8907dbef2fa38690e4a42ce11bc050c0","target":"graph","created_at":"2026-05-17T23:49:20Z","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":"Most previous learning-based visual odometry (VO) methods take VO as a pure tracking problem. In contrast, we present a VO framework by incorporating two additional components called Memory and Refining. The Memory component preserves global information by employing an adaptive and efficient selection strategy. The Refining component ameliorates previous results with the contexts stored in the Memory by adopting a spatial-temporal attention mechanism for feature distilling. Experiments on the KITTI and TUM-RGBD benchmark datasets demonstrate that our method outperforms state-of-the-art learnin","authors_text":"Fei Xue, Hongbin Zha, Junqiu Wang, Qiuyuan Wang, Shunkai Li, Xin Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-03T10:11:22Z","title":"Beyond Tracking: Selecting Memory and Refining Poses for Deep Visual Odometry"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.01892","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:df5dfaefbdda0408f6f1838787c91f6acbdf8391c6c2c69aed9cf2358a672ae9","target":"record","created_at":"2026-05-17T23:49:20Z","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":"a84d96cb56b6901a8846719a3a392ff4b777805222b5140aa0dd6350d0de23c6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-03T10:11:22Z","title_canon_sha256":"b3cc2ac93fc74c100d02e9cca8f8b18ba305e9e8795091ee64b8cd0f35f0cb4b"},"schema_version":"1.0","source":{"id":"1904.01892","kind":"arxiv","version":2}},"canonical_sha256":"7f0b429817c2f11d675147c92f7f853a1aa664534d4daec5343467a374d507c1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7f0b429817c2f11d675147c92f7f853a1aa664534d4daec5343467a374d507c1","first_computed_at":"2026-05-17T23:49:20.038181Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:49:20.038181Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+Jlf4Y2ZD6Bh6eJNB+OUaCub9BVaSlDLF36FKreechEp6dqGqYJXPPyJuAJe1l+S+ByOgrq+ngH5i/hJxMBwCQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:49:20.038859Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.01892","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:df5dfaefbdda0408f6f1838787c91f6acbdf8391c6c2c69aed9cf2358a672ae9","sha256:ec4044c94a0312cdfbab49ab5cc2a0fa8907dbef2fa38690e4a42ce11bc050c0"],"state_sha256":"88ae154db62178f315050e7303f952b62c60fc6055bd5d0137e6c24e43509691"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"un0Xumt1xv6yPb1wntVK4XxZlO5U/EsoKM/B5I06t+91ZZnmj8E+C5UmgsMrA1ax0PssdsOabg2OoRdQ3t/7Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-05T08:29:20.564165Z","bundle_sha256":"0921bb7160899faf6427bee3b481ef2aee6c1799e77bb1cd709fd18cdcae90b5"}}