{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:HBJOP37PZOXPS36HX7YNLQZVM5","short_pith_number":"pith:HBJOP37P","schema_version":"1.0","canonical_sha256":"3852e7efefcbaef96fc7bff0d5c335676aa16543023df0b514d4744bd12e569f","source":{"kind":"arxiv","id":"2411.08279","version":2},"attestation_state":"computed","paper":{"title":"MBA-SLAM: Motion Blur Aware Gaussian Splatting SLAM","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.CV","authors_text":"Lingzhe Zhao, Peidong Liu, Peng Wang, Shiyu Zhao, Yin Zhang","submitted_at":"2024-11-13T01:38:06Z","abstract_excerpt":"Emerging 3D scene representations, such as Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS), have demonstrated their effectiveness in Simultaneous Localization and Mapping (SLAM) for photo-realistic rendering, particularly when using high-quality video sequences as input. However, existing methods struggle with motion-blurred frames, which are common in real-world scenarios like low-light or long-exposure conditions. This often results in a significant reduction in both camera localization accuracy and map reconstruction quality. To address this challenge, we propose a dense visu"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2411.08279","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-11-13T01:38:06Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"5ec08af355300a7871b9907a1370c84b32fea4484ecb7b994e3c274bcf917042","abstract_canon_sha256":"5e3859cb0b1a490825cd9537bbff2b737998d780fb8e40fd4ebd92bd337b4501"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:50:28.852597Z","signature_b64":"VsEx6muGM3Jb7J+eH/YCeXCDRvfQzX6JIyxFfcre/txl/UIZz65aOJaFd19TPV79cgJcS7wZ2MREr72v1wJ+DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3852e7efefcbaef96fc7bff0d5c335676aa16543023df0b514d4744bd12e569f","last_reissued_at":"2026-07-05T11:50:28.852157Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:50:28.852157Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"MBA-SLAM: Motion Blur Aware Gaussian Splatting SLAM","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.CV","authors_text":"Lingzhe Zhao, Peidong Liu, Peng Wang, Shiyu Zhao, Yin Zhang","submitted_at":"2024-11-13T01:38:06Z","abstract_excerpt":"Emerging 3D scene representations, such as Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS), have demonstrated their effectiveness in Simultaneous Localization and Mapping (SLAM) for photo-realistic rendering, particularly when using high-quality video sequences as input. However, existing methods struggle with motion-blurred frames, which are common in real-world scenarios like low-light or long-exposure conditions. This often results in a significant reduction in both camera localization accuracy and map reconstruction quality. To address this challenge, we propose a dense visu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.08279","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2411.08279/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2411.08279","created_at":"2026-07-05T11:50:28.852212+00:00"},{"alias_kind":"arxiv_version","alias_value":"2411.08279v2","created_at":"2026-07-05T11:50:28.852212+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.08279","created_at":"2026-07-05T11:50:28.852212+00:00"},{"alias_kind":"pith_short_12","alias_value":"HBJOP37PZOXP","created_at":"2026-07-05T11:50:28.852212+00:00"},{"alias_kind":"pith_short_16","alias_value":"HBJOP37PZOXPS36H","created_at":"2026-07-05T11:50:28.852212+00:00"},{"alias_kind":"pith_short_8","alias_value":"HBJOP37P","created_at":"2026-07-05T11:50:28.852212+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/HBJOP37PZOXPS36HX7YNLQZVM5","json":"https://pith.science/pith/HBJOP37PZOXPS36HX7YNLQZVM5.json","graph_json":"https://pith.science/api/pith-number/HBJOP37PZOXPS36HX7YNLQZVM5/graph.json","events_json":"https://pith.science/api/pith-number/HBJOP37PZOXPS36HX7YNLQZVM5/events.json","paper":"https://pith.science/paper/HBJOP37P"},"agent_actions":{"view_html":"https://pith.science/pith/HBJOP37PZOXPS36HX7YNLQZVM5","download_json":"https://pith.science/pith/HBJOP37PZOXPS36HX7YNLQZVM5.json","view_paper":"https://pith.science/paper/HBJOP37P","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2411.08279&json=true","fetch_graph":"https://pith.science/api/pith-number/HBJOP37PZOXPS36HX7YNLQZVM5/graph.json","fetch_events":"https://pith.science/api/pith-number/HBJOP37PZOXPS36HX7YNLQZVM5/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HBJOP37PZOXPS36HX7YNLQZVM5/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HBJOP37PZOXPS36HX7YNLQZVM5/action/storage_attestation","attest_author":"https://pith.science/pith/HBJOP37PZOXPS36HX7YNLQZVM5/action/author_attestation","sign_citation":"https://pith.science/pith/HBJOP37PZOXPS36HX7YNLQZVM5/action/citation_signature","submit_replication":"https://pith.science/pith/HBJOP37PZOXPS36HX7YNLQZVM5/action/replication_record"}},"created_at":"2026-07-05T11:50:28.852212+00:00","updated_at":"2026-07-05T11:50:28.852212+00:00"}