{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:KWQSKTNRZPZ3WPE67JSMAP2WOC","short_pith_number":"pith:KWQSKTNR","schema_version":"1.0","canonical_sha256":"55a1254db1cbf3bb3c9efa64c03f567095361686fead93c6882a6146cb56daaa","source":{"kind":"arxiv","id":"2505.15860","version":1},"attestation_state":"computed","paper":{"title":"RadarRGBD A Multi-Sensor Fusion Dataset for Perception with RGB-D and mmWave Radar","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"eess.IV","authors_text":"Ao Guo, Bin Yang, Guidong He, Jiandong Ye, Tieshuai Song","submitted_at":"2025-05-21T05:30:04Z","abstract_excerpt":"Multi-sensor fusion has significant potential in perception tasks for both indoor and outdoor environments. Especially under challenging conditions such as adverse weather and low-light environments, the combined use of millimeter-wave radar and RGB-D sensors has shown distinct advantages. However, existing multi-sensor datasets in the fields of autonomous driving and robotics often lack high-quality millimeter-wave radar data. To address this gap, we present a new multi-sensor dataset:RadarRGBD. This dataset includes RGB-D data, millimeter-wave radar point clouds, and raw radar matrices, cove"},"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":"2505.15860","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2025-05-21T05:30:04Z","cross_cats_sorted":[],"title_canon_sha256":"312cd0ddef955402af174f430b76b70a006770a6df7ae3114e19f412930e761c","abstract_canon_sha256":"cc1b11cdd902680a373ce0858be11108df59faf648d57af89eb6ff6c178d4a3f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:07:26.496192Z","signature_b64":"OfUaI9Uj3Z0x2Z+5o48MaaVlHUrVtMnYwTgZsjesjQf+q9y0raUbeBwh5o3fmMugA06iKy+kJ8KiTFjFpL09BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"55a1254db1cbf3bb3c9efa64c03f567095361686fead93c6882a6146cb56daaa","last_reissued_at":"2026-07-05T11:07:26.495792Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:07:26.495792Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"RadarRGBD A Multi-Sensor Fusion Dataset for Perception with RGB-D and mmWave Radar","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"eess.IV","authors_text":"Ao Guo, Bin Yang, Guidong He, Jiandong Ye, Tieshuai Song","submitted_at":"2025-05-21T05:30:04Z","abstract_excerpt":"Multi-sensor fusion has significant potential in perception tasks for both indoor and outdoor environments. Especially under challenging conditions such as adverse weather and low-light environments, the combined use of millimeter-wave radar and RGB-D sensors has shown distinct advantages. However, existing multi-sensor datasets in the fields of autonomous driving and robotics often lack high-quality millimeter-wave radar data. To address this gap, we present a new multi-sensor dataset:RadarRGBD. This dataset includes RGB-D data, millimeter-wave radar point clouds, and raw radar matrices, cove"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.15860","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/2505.15860/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":"2505.15860","created_at":"2026-07-05T11:07:26.495847+00:00"},{"alias_kind":"arxiv_version","alias_value":"2505.15860v1","created_at":"2026-07-05T11:07:26.495847+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.15860","created_at":"2026-07-05T11:07:26.495847+00:00"},{"alias_kind":"pith_short_12","alias_value":"KWQSKTNRZPZ3","created_at":"2026-07-05T11:07:26.495847+00:00"},{"alias_kind":"pith_short_16","alias_value":"KWQSKTNRZPZ3WPE6","created_at":"2026-07-05T11:07:26.495847+00:00"},{"alias_kind":"pith_short_8","alias_value":"KWQSKTNR","created_at":"2026-07-05T11:07:26.495847+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/KWQSKTNRZPZ3WPE67JSMAP2WOC","json":"https://pith.science/pith/KWQSKTNRZPZ3WPE67JSMAP2WOC.json","graph_json":"https://pith.science/api/pith-number/KWQSKTNRZPZ3WPE67JSMAP2WOC/graph.json","events_json":"https://pith.science/api/pith-number/KWQSKTNRZPZ3WPE67JSMAP2WOC/events.json","paper":"https://pith.science/paper/KWQSKTNR"},"agent_actions":{"view_html":"https://pith.science/pith/KWQSKTNRZPZ3WPE67JSMAP2WOC","download_json":"https://pith.science/pith/KWQSKTNRZPZ3WPE67JSMAP2WOC.json","view_paper":"https://pith.science/paper/KWQSKTNR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2505.15860&json=true","fetch_graph":"https://pith.science/api/pith-number/KWQSKTNRZPZ3WPE67JSMAP2WOC/graph.json","fetch_events":"https://pith.science/api/pith-number/KWQSKTNRZPZ3WPE67JSMAP2WOC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/KWQSKTNRZPZ3WPE67JSMAP2WOC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/KWQSKTNRZPZ3WPE67JSMAP2WOC/action/storage_attestation","attest_author":"https://pith.science/pith/KWQSKTNRZPZ3WPE67JSMAP2WOC/action/author_attestation","sign_citation":"https://pith.science/pith/KWQSKTNRZPZ3WPE67JSMAP2WOC/action/citation_signature","submit_replication":"https://pith.science/pith/KWQSKTNRZPZ3WPE67JSMAP2WOC/action/replication_record"}},"created_at":"2026-07-05T11:07:26.495847+00:00","updated_at":"2026-07-05T11:07:26.495847+00:00"}