{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:LL5SINZBRUM477DQIJ7FEBYSHL","short_pith_number":"pith:LL5SINZB","canonical_record":{"source":{"id":"2405.16754","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-05-27T01:54:07Z","cross_cats_sorted":[],"title_canon_sha256":"dd36d883af694bd4a413488930b51a15742718e99aabed6834ace2b189260621","abstract_canon_sha256":"d47e063b9b8c92d7dac5cdd58e43d70d4e225c1ac2a77033da3bdaafaaa11ce6"},"schema_version":"1.0"},"canonical_sha256":"5afb2437218d19cffc70427e5207123af1841340339730818d3d69138bab0672","source":{"kind":"arxiv","id":"2405.16754","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.16754","created_at":"2026-07-05T08:23:35Z"},{"alias_kind":"arxiv_version","alias_value":"2405.16754v1","created_at":"2026-07-05T08:23:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.16754","created_at":"2026-07-05T08:23:35Z"},{"alias_kind":"pith_short_12","alias_value":"LL5SINZBRUM4","created_at":"2026-07-05T08:23:35Z"},{"alias_kind":"pith_short_16","alias_value":"LL5SINZBRUM477DQ","created_at":"2026-07-05T08:23:35Z"},{"alias_kind":"pith_short_8","alias_value":"LL5SINZB","created_at":"2026-07-05T08:23:35Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:LL5SINZBRUM477DQIJ7FEBYSHL","target":"record","payload":{"canonical_record":{"source":{"id":"2405.16754","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-05-27T01:54:07Z","cross_cats_sorted":[],"title_canon_sha256":"dd36d883af694bd4a413488930b51a15742718e99aabed6834ace2b189260621","abstract_canon_sha256":"d47e063b9b8c92d7dac5cdd58e43d70d4e225c1ac2a77033da3bdaafaaa11ce6"},"schema_version":"1.0"},"canonical_sha256":"5afb2437218d19cffc70427e5207123af1841340339730818d3d69138bab0672","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:23:35.016141Z","signature_b64":"Nk+H5dH7s5MuGkz4y2ZKIsvUGxpEjqTBh2sqXDjjz1N7GC8a14M5bfyrnPt3pW4F0b4utcGFP3SLP4qP+stWBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5afb2437218d19cffc70427e5207123af1841340339730818d3d69138bab0672","last_reissued_at":"2026-07-05T08:23:35.015655Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:23:35.015655Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2405.16754","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":"2026-07-05T08:23:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FczDLwhjsclfiDdRSYMZciUvQKiOfREMQ6wv8DrM+4RJrx2qhaxJiDPxfYIvAwKA0eWbsAUqsdwCsHt5QnQhDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T11:10:23.587787Z"},"content_sha256":"b12fcfd0b580ce3749c90d667d5b87f80453c59432cd662ca5eafe6cf8a2c468","schema_version":"1.0","event_id":"sha256:b12fcfd0b580ce3749c90d667d5b87f80453c59432cd662ca5eafe6cf8a2c468"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:LL5SINZBRUM477DQIJ7FEBYSHL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Adaptive VIO: Deep Visual-Inertial Odometry with Online Continual Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Hongbin Zha, Wugen Zhou, Yingdian Cao, Youqi Pan","submitted_at":"2024-05-27T01:54:07Z","abstract_excerpt":"Visual-inertial odometry (VIO) has demonstrated remarkable success due to its low-cost and complementary sensors. However, existing VIO methods lack the generalization ability to adjust to different environments and sensor attributes. In this paper, we propose Adaptive VIO, a new monocular visual-inertial odometry that combines online continual learning with traditional nonlinear optimization. Adaptive VIO comprises two networks to predict visual correspondence and IMU bias. Unlike end-to-end approaches that use networks to fuse the features from two modalities (camera and IMU) and predict pos"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.16754","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/2405.16754/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":"2026-07-05T08:23:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"a3Ht9owngWg5owW2HAbaG2jeY8kU6O5I4glhNUu3M2c1ExXRtsJFbsCfgldKyPYWFKhJO8OM7DLYYQBjzXTyBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T11:10:23.588737Z"},"content_sha256":"5189b8738806df376af39791f24e543fcd7df549fee1f20580962f3812c44966","schema_version":"1.0","event_id":"sha256:5189b8738806df376af39791f24e543fcd7df549fee1f20580962f3812c44966"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LL5SINZBRUM477DQIJ7FEBYSHL/bundle.json","state_url":"https://pith.science/pith/LL5SINZBRUM477DQIJ7FEBYSHL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LL5SINZBRUM477DQIJ7FEBYSHL/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":"2026-08-11T11:10:23Z","links":{"resolver":"https://pith.science/pith/LL5SINZBRUM477DQIJ7FEBYSHL","bundle":"https://pith.science/pith/LL5SINZBRUM477DQIJ7FEBYSHL/bundle.json","state":"https://pith.science/pith/LL5SINZBRUM477DQIJ7FEBYSHL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LL5SINZBRUM477DQIJ7FEBYSHL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:LL5SINZBRUM477DQIJ7FEBYSHL","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":"d47e063b9b8c92d7dac5cdd58e43d70d4e225c1ac2a77033da3bdaafaaa11ce6","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-05-27T01:54:07Z","title_canon_sha256":"dd36d883af694bd4a413488930b51a15742718e99aabed6834ace2b189260621"},"schema_version":"1.0","source":{"id":"2405.16754","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.16754","created_at":"2026-07-05T08:23:35Z"},{"alias_kind":"arxiv_version","alias_value":"2405.16754v1","created_at":"2026-07-05T08:23:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.16754","created_at":"2026-07-05T08:23:35Z"},{"alias_kind":"pith_short_12","alias_value":"LL5SINZBRUM4","created_at":"2026-07-05T08:23:35Z"},{"alias_kind":"pith_short_16","alias_value":"LL5SINZBRUM477DQ","created_at":"2026-07-05T08:23:35Z"},{"alias_kind":"pith_short_8","alias_value":"LL5SINZB","created_at":"2026-07-05T08:23:35Z"}],"graph_snapshots":[{"event_id":"sha256:5189b8738806df376af39791f24e543fcd7df549fee1f20580962f3812c44966","target":"graph","created_at":"2026-07-05T08:23:35Z","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/2405.16754/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Visual-inertial odometry (VIO) has demonstrated remarkable success due to its low-cost and complementary sensors. However, existing VIO methods lack the generalization ability to adjust to different environments and sensor attributes. In this paper, we propose Adaptive VIO, a new monocular visual-inertial odometry that combines online continual learning with traditional nonlinear optimization. Adaptive VIO comprises two networks to predict visual correspondence and IMU bias. Unlike end-to-end approaches that use networks to fuse the features from two modalities (camera and IMU) and predict pos","authors_text":"Hongbin Zha, Wugen Zhou, Yingdian Cao, Youqi Pan","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-05-27T01:54:07Z","title":"Adaptive VIO: Deep Visual-Inertial Odometry with Online Continual Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.16754","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:b12fcfd0b580ce3749c90d667d5b87f80453c59432cd662ca5eafe6cf8a2c468","target":"record","created_at":"2026-07-05T08:23:35Z","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":"d47e063b9b8c92d7dac5cdd58e43d70d4e225c1ac2a77033da3bdaafaaa11ce6","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-05-27T01:54:07Z","title_canon_sha256":"dd36d883af694bd4a413488930b51a15742718e99aabed6834ace2b189260621"},"schema_version":"1.0","source":{"id":"2405.16754","kind":"arxiv","version":1}},"canonical_sha256":"5afb2437218d19cffc70427e5207123af1841340339730818d3d69138bab0672","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5afb2437218d19cffc70427e5207123af1841340339730818d3d69138bab0672","first_computed_at":"2026-07-05T08:23:35.015655Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:23:35.015655Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Nk+H5dH7s5MuGkz4y2ZKIsvUGxpEjqTBh2sqXDjjz1N7GC8a14M5bfyrnPt3pW4F0b4utcGFP3SLP4qP+stWBA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:23:35.016141Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.16754","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b12fcfd0b580ce3749c90d667d5b87f80453c59432cd662ca5eafe6cf8a2c468","sha256:5189b8738806df376af39791f24e543fcd7df549fee1f20580962f3812c44966"],"state_sha256":"afe304e90f345b36ee9e4eff644c6994ee0a538a8ca478e1f624c6afd5575110"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8EEzwJKE8Z68p6ZmDy/MGJQhe0mxqc1Nu3XDF4kH8g90TS/NiYieSiy4x1Iv2Q9RpH1i18dyQzfUyzI904VZBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T11:10:23.595212Z","bundle_sha256":"c40cd5ff76f220e9841d56545edbe6307eee9d1482929eb8b1cc5958271f9377"}}