{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:KDEUZTPVB6S7UKJIQNXXZXTBMM","short_pith_number":"pith:KDEUZTPV","schema_version":"1.0","canonical_sha256":"50c94ccdf50fa5fa2928836f7cde61633d5c5c9159febc789093bd7fd87f320b","source":{"kind":"arxiv","id":"2607.04661","version":1},"attestation_state":"computed","paper":{"title":"Targeted Structure Completion for Sparse-View 3D Reconstruction in Autonomous Driving","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Chao Ma, Guoqing Wang, Liping Hou, Pin Tang, Xiangxuan Ren","submitted_at":"2026-07-06T04:31:45Z","abstract_excerpt":"Reconstructing 3D scene structures from sparse, low-overlap observations remains a fundamental challenge in autonomous driving. Recent state-of-the-art frameworks achieve promising results by incorporating voxel-based Gaussians, but incur substantial computational redundancy due to a uniform volumetric processing strategy. To bridge the gap between the efficiency of pixel-based Gaussian methods and the structural completeness of voxel-based Gaussian approaches, we propose FocusGS, a simple yet effective framework that shifts the paradigm from global densification to targeted structural complet"},"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":"2607.04661","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-07-06T04:31:45Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"708b122c697d7c1413b5ca86b465083ec37c59cf1fd2de9cd1fc27eab9456d7e","abstract_canon_sha256":"f500ead21fddc9f8e18151dbb62c4aa0917aa0177c44785de6a79ffc71868e38"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-07T02:19:29.988907Z","signature_b64":"InXxamnmugQNYLEyq38mOc3luAU/RVJwM1X57at3I+G1Fq7lzl7U4yhj+A9H68e0t3U21onFdPBUFyi7zXA2DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"50c94ccdf50fa5fa2928836f7cde61633d5c5c9159febc789093bd7fd87f320b","last_reissued_at":"2026-07-07T02:19:29.988222Z","signature_status":"signed_v1","first_computed_at":"2026-07-07T02:19:29.988222Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Targeted Structure Completion for Sparse-View 3D Reconstruction in Autonomous Driving","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Chao Ma, Guoqing Wang, Liping Hou, Pin Tang, Xiangxuan Ren","submitted_at":"2026-07-06T04:31:45Z","abstract_excerpt":"Reconstructing 3D scene structures from sparse, low-overlap observations remains a fundamental challenge in autonomous driving. Recent state-of-the-art frameworks achieve promising results by incorporating voxel-based Gaussians, but incur substantial computational redundancy due to a uniform volumetric processing strategy. To bridge the gap between the efficiency of pixel-based Gaussian methods and the structural completeness of voxel-based Gaussian approaches, we propose FocusGS, a simple yet effective framework that shifts the paradigm from global densification to targeted structural complet"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.04661","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/2607.04661/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":"2607.04661","created_at":"2026-07-07T02:19:29.988327+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.04661v1","created_at":"2026-07-07T02:19:29.988327+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.04661","created_at":"2026-07-07T02:19:29.988327+00:00"},{"alias_kind":"pith_short_12","alias_value":"KDEUZTPVB6S7","created_at":"2026-07-07T02:19:29.988327+00:00"},{"alias_kind":"pith_short_16","alias_value":"KDEUZTPVB6S7UKJI","created_at":"2026-07-07T02:19:29.988327+00:00"},{"alias_kind":"pith_short_8","alias_value":"KDEUZTPV","created_at":"2026-07-07T02:19:29.988327+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/KDEUZTPVB6S7UKJIQNXXZXTBMM","json":"https://pith.science/pith/KDEUZTPVB6S7UKJIQNXXZXTBMM.json","graph_json":"https://pith.science/api/pith-number/KDEUZTPVB6S7UKJIQNXXZXTBMM/graph.json","events_json":"https://pith.science/api/pith-number/KDEUZTPVB6S7UKJIQNXXZXTBMM/events.json","paper":"https://pith.science/paper/KDEUZTPV"},"agent_actions":{"view_html":"https://pith.science/pith/KDEUZTPVB6S7UKJIQNXXZXTBMM","download_json":"https://pith.science/pith/KDEUZTPVB6S7UKJIQNXXZXTBMM.json","view_paper":"https://pith.science/paper/KDEUZTPV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.04661&json=true","fetch_graph":"https://pith.science/api/pith-number/KDEUZTPVB6S7UKJIQNXXZXTBMM/graph.json","fetch_events":"https://pith.science/api/pith-number/KDEUZTPVB6S7UKJIQNXXZXTBMM/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/KDEUZTPVB6S7UKJIQNXXZXTBMM/action/timestamp_anchor","attest_storage":"https://pith.science/pith/KDEUZTPVB6S7UKJIQNXXZXTBMM/action/storage_attestation","attest_author":"https://pith.science/pith/KDEUZTPVB6S7UKJIQNXXZXTBMM/action/author_attestation","sign_citation":"https://pith.science/pith/KDEUZTPVB6S7UKJIQNXXZXTBMM/action/citation_signature","submit_replication":"https://pith.science/pith/KDEUZTPVB6S7UKJIQNXXZXTBMM/action/replication_record"}},"created_at":"2026-07-07T02:19:29.988327+00:00","updated_at":"2026-07-07T02:19:29.988327+00:00"}