{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:5KPH7PRI4SSSMGVP5Z2LC66ULY","short_pith_number":"pith:5KPH7PRI","schema_version":"1.0","canonical_sha256":"ea9e7fbe28e4a5261aafee74b17bd45e1fd0c2160c642da7640bf90987bf4832","source":{"kind":"arxiv","id":"2409.12899","version":1},"attestation_state":"computed","paper":{"title":"LI-GS: Gaussian Splatting with LiDAR Incorporated for Accurate Large-Scale Reconstruction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Changjian Jiang, Kele Shao, Rong Xiong, Ruilan Gao, Yue Wang, Yu Zhang","submitted_at":"2024-09-19T16:41:05Z","abstract_excerpt":"Large-scale 3D reconstruction is critical in the field of robotics, and the potential of 3D Gaussian Splatting (3DGS) for achieving accurate object-level reconstruction has been demonstrated. However, ensuring geometric accuracy in outdoor and unbounded scenes remains a significant challenge. This study introduces LI-GS, a reconstruction system that incorporates LiDAR and Gaussian Splatting to enhance geometric accuracy in large-scale scenes. 2D Gaussain surfels are employed as the map representation to enhance surface alignment. Additionally, a novel modeling method is proposed to convert LiD"},"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":"2409.12899","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-09-19T16:41:05Z","cross_cats_sorted":[],"title_canon_sha256":"93def0b6a62f9925d4e68123d5259789562b2101afc92ee10964b1591c2b7e23","abstract_canon_sha256":"b9c54d89560249de7654a00fe7c4ed0a68afe85cbeb495764c3e4bea1d52a6c6"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:09:13.685699Z","signature_b64":"PjpzV0L6js0lMhkAt5hC5AQEwz07X5E37Bl/CrD3S/M4rcM/K2tq2/Q+/xidgalvz1ncVKRpQNysHL4PfEl5BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ea9e7fbe28e4a5261aafee74b17bd45e1fd0c2160c642da7640bf90987bf4832","last_reissued_at":"2026-07-05T09:09:13.685132Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:09:13.685132Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"LI-GS: Gaussian Splatting with LiDAR Incorporated for Accurate Large-Scale Reconstruction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Changjian Jiang, Kele Shao, Rong Xiong, Ruilan Gao, Yue Wang, Yu Zhang","submitted_at":"2024-09-19T16:41:05Z","abstract_excerpt":"Large-scale 3D reconstruction is critical in the field of robotics, and the potential of 3D Gaussian Splatting (3DGS) for achieving accurate object-level reconstruction has been demonstrated. However, ensuring geometric accuracy in outdoor and unbounded scenes remains a significant challenge. This study introduces LI-GS, a reconstruction system that incorporates LiDAR and Gaussian Splatting to enhance geometric accuracy in large-scale scenes. 2D Gaussain surfels are employed as the map representation to enhance surface alignment. Additionally, a novel modeling method is proposed to convert LiD"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.12899","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/2409.12899/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":"2409.12899","created_at":"2026-07-05T09:09:13.685191+00:00"},{"alias_kind":"arxiv_version","alias_value":"2409.12899v1","created_at":"2026-07-05T09:09:13.685191+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.12899","created_at":"2026-07-05T09:09:13.685191+00:00"},{"alias_kind":"pith_short_12","alias_value":"5KPH7PRI4SSS","created_at":"2026-07-05T09:09:13.685191+00:00"},{"alias_kind":"pith_short_16","alias_value":"5KPH7PRI4SSSMGVP","created_at":"2026-07-05T09:09:13.685191+00:00"},{"alias_kind":"pith_short_8","alias_value":"5KPH7PRI","created_at":"2026-07-05T09:09:13.685191+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/5KPH7PRI4SSSMGVP5Z2LC66ULY","json":"https://pith.science/pith/5KPH7PRI4SSSMGVP5Z2LC66ULY.json","graph_json":"https://pith.science/api/pith-number/5KPH7PRI4SSSMGVP5Z2LC66ULY/graph.json","events_json":"https://pith.science/api/pith-number/5KPH7PRI4SSSMGVP5Z2LC66ULY/events.json","paper":"https://pith.science/paper/5KPH7PRI"},"agent_actions":{"view_html":"https://pith.science/pith/5KPH7PRI4SSSMGVP5Z2LC66ULY","download_json":"https://pith.science/pith/5KPH7PRI4SSSMGVP5Z2LC66ULY.json","view_paper":"https://pith.science/paper/5KPH7PRI","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2409.12899&json=true","fetch_graph":"https://pith.science/api/pith-number/5KPH7PRI4SSSMGVP5Z2LC66ULY/graph.json","fetch_events":"https://pith.science/api/pith-number/5KPH7PRI4SSSMGVP5Z2LC66ULY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5KPH7PRI4SSSMGVP5Z2LC66ULY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5KPH7PRI4SSSMGVP5Z2LC66ULY/action/storage_attestation","attest_author":"https://pith.science/pith/5KPH7PRI4SSSMGVP5Z2LC66ULY/action/author_attestation","sign_citation":"https://pith.science/pith/5KPH7PRI4SSSMGVP5Z2LC66ULY/action/citation_signature","submit_replication":"https://pith.science/pith/5KPH7PRI4SSSMGVP5Z2LC66ULY/action/replication_record"}},"created_at":"2026-07-05T09:09:13.685191+00:00","updated_at":"2026-07-05T09:09:13.685191+00:00"}