{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:3PX5CQPDWURSWFHDFWW5UIG4WQ","short_pith_number":"pith:3PX5CQPD","schema_version":"1.0","canonical_sha256":"dbefd141e3b5232b14e32dadda20dcb41397122e7e00e681d5799ecec343c464","source":{"kind":"arxiv","id":"2501.09203","version":2},"attestation_state":"computed","paper":{"title":"3D Modeling and Automated Measurement of Concrete Cracks via Segment Anything Refinement and Visual Inertial LiDAR Fusion","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.CV","authors_text":"Chun Li, Jiapeng Yao, Pengru Deng, Su Wang, Varun Ojha, Xinrun Li, Xuhui He","submitted_at":"2025-01-15T23:36:05Z","abstract_excerpt":"Visual-Spatial Systems has become increasingly essential in concrete crack inspection. However, existing methods often lacks adaptability to diverse scenarios, exhibits limited robustness in image-based approaches, and struggles with curved or complex geometries. To address these limitations, an innovative framework for two-dimensional (2D) crack detection, three-dimensional (3D) reconstruction, and 3D automatic crack measurement was proposed by integrating computer vision technologies and multi-modal Simultaneous localization and mapping (SLAM) in this study. Firstly, building on a base DeepL"},"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":"2501.09203","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-01-15T23:36:05Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"f98b2f8c8b9f6a8d811d8d493d9f8a240def7c148baad48b3495ceb37b148deb","abstract_canon_sha256":"6e3cfae46b5388a66c20a0bcc741b9043231fe7d34b6bf87548a75012b320e81"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T01:04:51.692906Z","signature_b64":"wPzah8a7sHanXOp546tHx2rtHMqCUDmGRZNEbV3s+XAv8lV2njI/vhN9NdP+jZxDX0iSWJKMrUyTGkYxwjftBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dbefd141e3b5232b14e32dadda20dcb41397122e7e00e681d5799ecec343c464","last_reissued_at":"2026-05-20T01:04:51.691979Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T01:04:51.691979Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"3D Modeling and Automated Measurement of Concrete Cracks via Segment Anything Refinement and Visual Inertial LiDAR Fusion","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.CV","authors_text":"Chun Li, Jiapeng Yao, Pengru Deng, Su Wang, Varun Ojha, Xinrun Li, Xuhui He","submitted_at":"2025-01-15T23:36:05Z","abstract_excerpt":"Visual-Spatial Systems has become increasingly essential in concrete crack inspection. However, existing methods often lacks adaptability to diverse scenarios, exhibits limited robustness in image-based approaches, and struggles with curved or complex geometries. To address these limitations, an innovative framework for two-dimensional (2D) crack detection, three-dimensional (3D) reconstruction, and 3D automatic crack measurement was proposed by integrating computer vision technologies and multi-modal Simultaneous localization and mapping (SLAM) in this study. Firstly, building on a base DeepL"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.09203","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/2501.09203/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":"2501.09203","created_at":"2026-05-20T01:04:51.692104+00:00"},{"alias_kind":"arxiv_version","alias_value":"2501.09203v2","created_at":"2026-05-20T01:04:51.692104+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.09203","created_at":"2026-05-20T01:04:51.692104+00:00"},{"alias_kind":"pith_short_12","alias_value":"3PX5CQPDWURS","created_at":"2026-05-20T01:04:51.692104+00:00"},{"alias_kind":"pith_short_16","alias_value":"3PX5CQPDWURSWFHD","created_at":"2026-05-20T01:04:51.692104+00:00"},{"alias_kind":"pith_short_8","alias_value":"3PX5CQPD","created_at":"2026-05-20T01:04:51.692104+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/3PX5CQPDWURSWFHDFWW5UIG4WQ","json":"https://pith.science/pith/3PX5CQPDWURSWFHDFWW5UIG4WQ.json","graph_json":"https://pith.science/api/pith-number/3PX5CQPDWURSWFHDFWW5UIG4WQ/graph.json","events_json":"https://pith.science/api/pith-number/3PX5CQPDWURSWFHDFWW5UIG4WQ/events.json","paper":"https://pith.science/paper/3PX5CQPD"},"agent_actions":{"view_html":"https://pith.science/pith/3PX5CQPDWURSWFHDFWW5UIG4WQ","download_json":"https://pith.science/pith/3PX5CQPDWURSWFHDFWW5UIG4WQ.json","view_paper":"https://pith.science/paper/3PX5CQPD","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2501.09203&json=true","fetch_graph":"https://pith.science/api/pith-number/3PX5CQPDWURSWFHDFWW5UIG4WQ/graph.json","fetch_events":"https://pith.science/api/pith-number/3PX5CQPDWURSWFHDFWW5UIG4WQ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3PX5CQPDWURSWFHDFWW5UIG4WQ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3PX5CQPDWURSWFHDFWW5UIG4WQ/action/storage_attestation","attest_author":"https://pith.science/pith/3PX5CQPDWURSWFHDFWW5UIG4WQ/action/author_attestation","sign_citation":"https://pith.science/pith/3PX5CQPDWURSWFHDFWW5UIG4WQ/action/citation_signature","submit_replication":"https://pith.science/pith/3PX5CQPDWURSWFHDFWW5UIG4WQ/action/replication_record"}},"created_at":"2026-05-20T01:04:51.692104+00:00","updated_at":"2026-05-20T01:04:51.692104+00:00"}