{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:LOOIQEGNUWPKIZ26TFS4UIM3DG","short_pith_number":"pith:LOOIQEGN","schema_version":"1.0","canonical_sha256":"5b9c8810cda59ea4675e9965ca219b19927c8d1be041facb9651dc0161db01ad","source":{"kind":"arxiv","id":"2606.26743","version":1},"attestation_state":"computed","paper":{"title":"Depth-Semantic Alignment and Affinity-Guided Fusion for Structured Radar Point Cloud Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Amjad Hussain, Chunyi Song, Fuyuan Ai, Wenjie Liu, Xin Qiu, YuChen Tan, Zecheng Li","submitted_at":"2026-06-25T08:28:18Z","abstract_excerpt":"Point clouds are an important carrier of three-dimensional spatial information, and their quality directly affects the performance of downstream perception tasks such as object detection and tracking. However, millimeter-wave radar point clouds are typically sparse, noisy, and structurally incomplete. To address these limitations, this paper proposes a multimodal point cloud generation method based on vision-radar fusion. The proposed method leverages image semantic information to impose structural constraints and achieve spatial alignment for radar point clouds, while incorporating a sparse c"},"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":"2606.26743","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-25T08:28:18Z","cross_cats_sorted":[],"title_canon_sha256":"deadd5d9205775f23028118bd2d9e83edb94cd8ac31f3a8dd01e247a2c53ccdb","abstract_canon_sha256":"ffe0441c5ba0151eb82bb6837d18910fa286730ce275db33a11740da4acd2293"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-26T01:15:58.557354Z","signature_b64":"51nENKbUNsChDYD16LPokWeEQYFEZ2d5yCVF/zPzM7PcnGzJRL5FA5oTf6LlSqzP4TNFfPZzdlfzk6MimgSiAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5b9c8810cda59ea4675e9965ca219b19927c8d1be041facb9651dc0161db01ad","last_reissued_at":"2026-06-26T01:15:58.556963Z","signature_status":"signed_v1","first_computed_at":"2026-06-26T01:15:58.556963Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Depth-Semantic Alignment and Affinity-Guided Fusion for Structured Radar Point Cloud Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Amjad Hussain, Chunyi Song, Fuyuan Ai, Wenjie Liu, Xin Qiu, YuChen Tan, Zecheng Li","submitted_at":"2026-06-25T08:28:18Z","abstract_excerpt":"Point clouds are an important carrier of three-dimensional spatial information, and their quality directly affects the performance of downstream perception tasks such as object detection and tracking. However, millimeter-wave radar point clouds are typically sparse, noisy, and structurally incomplete. To address these limitations, this paper proposes a multimodal point cloud generation method based on vision-radar fusion. The proposed method leverages image semantic information to impose structural constraints and achieve spatial alignment for radar point clouds, while incorporating a sparse c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.26743","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/2606.26743/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":"2606.26743","created_at":"2026-06-26T01:15:58.557019+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.26743v1","created_at":"2026-06-26T01:15:58.557019+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.26743","created_at":"2026-06-26T01:15:58.557019+00:00"},{"alias_kind":"pith_short_12","alias_value":"LOOIQEGNUWPK","created_at":"2026-06-26T01:15:58.557019+00:00"},{"alias_kind":"pith_short_16","alias_value":"LOOIQEGNUWPKIZ26","created_at":"2026-06-26T01:15:58.557019+00:00"},{"alias_kind":"pith_short_8","alias_value":"LOOIQEGN","created_at":"2026-06-26T01:15:58.557019+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/LOOIQEGNUWPKIZ26TFS4UIM3DG","json":"https://pith.science/pith/LOOIQEGNUWPKIZ26TFS4UIM3DG.json","graph_json":"https://pith.science/api/pith-number/LOOIQEGNUWPKIZ26TFS4UIM3DG/graph.json","events_json":"https://pith.science/api/pith-number/LOOIQEGNUWPKIZ26TFS4UIM3DG/events.json","paper":"https://pith.science/paper/LOOIQEGN"},"agent_actions":{"view_html":"https://pith.science/pith/LOOIQEGNUWPKIZ26TFS4UIM3DG","download_json":"https://pith.science/pith/LOOIQEGNUWPKIZ26TFS4UIM3DG.json","view_paper":"https://pith.science/paper/LOOIQEGN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.26743&json=true","fetch_graph":"https://pith.science/api/pith-number/LOOIQEGNUWPKIZ26TFS4UIM3DG/graph.json","fetch_events":"https://pith.science/api/pith-number/LOOIQEGNUWPKIZ26TFS4UIM3DG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/LOOIQEGNUWPKIZ26TFS4UIM3DG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/LOOIQEGNUWPKIZ26TFS4UIM3DG/action/storage_attestation","attest_author":"https://pith.science/pith/LOOIQEGNUWPKIZ26TFS4UIM3DG/action/author_attestation","sign_citation":"https://pith.science/pith/LOOIQEGNUWPKIZ26TFS4UIM3DG/action/citation_signature","submit_replication":"https://pith.science/pith/LOOIQEGNUWPKIZ26TFS4UIM3DG/action/replication_record"}},"created_at":"2026-06-26T01:15:58.557019+00:00","updated_at":"2026-06-26T01:15:58.557019+00:00"}