{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:TJ6GHHJEGBKB4OWBLUEVTF2W4K","short_pith_number":"pith:TJ6GHHJE","schema_version":"1.0","canonical_sha256":"9a7c639d2430541e3ac15d09599756e284cb5dae5ce2167d68c9d666d2acf914","source":{"kind":"arxiv","id":"2107.04286","version":3},"attestation_state":"computed","paper":{"title":"Capturing, Reconstructing, and Simulating: the UrbanScene3D Dataset","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.GR"],"primary_cat":"cs.CV","authors_text":"Hui Huang, Ke Xie, Liqiang Lin, Xingguang Yan, Yilin Liu, Yue Hu","submitted_at":"2021-07-09T07:56:46Z","abstract_excerpt":"We present UrbanScene3D, a large-scale data platform for research of urban scene perception and reconstruction. UrbanScene3D contains over 128k high-resolution images covering 16 scenes including large-scale real urban regions and synthetic cities with 136 km^2 area in total. The dataset also contains high-precision LiDAR scans and hundreds of image sets with different observation patterns, which provide a comprehensive benchmark to design and evaluate aerial path planning and 3D reconstruction algorithms. In addition, the dataset, which is built on Unreal Engine and Airsim simulator together "},"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":"2107.04286","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-07-09T07:56:46Z","cross_cats_sorted":["cs.GR"],"title_canon_sha256":"1abf7dfce2f95a88840d2f26c5b44c264cf70c544cb641d1c46c600800015cfd","abstract_canon_sha256":"7a196ea9d2041d45ccdd1e528267b8ff5b7680a8074097887e633f01bb9c1a57"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:41:09.928818Z","signature_b64":"ZwTGRRiaREGnkpPIDidel8UAPKiEJgw6CJ32mmSEpgWR55lh8Da9ehaFljUfbUU6O2WUJZZi3bkqbs/vpPyLDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9a7c639d2430541e3ac15d09599756e284cb5dae5ce2167d68c9d666d2acf914","last_reissued_at":"2026-07-05T04:41:09.928366Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:41:09.928366Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Capturing, Reconstructing, and Simulating: the UrbanScene3D Dataset","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.GR"],"primary_cat":"cs.CV","authors_text":"Hui Huang, Ke Xie, Liqiang Lin, Xingguang Yan, Yilin Liu, Yue Hu","submitted_at":"2021-07-09T07:56:46Z","abstract_excerpt":"We present UrbanScene3D, a large-scale data platform for research of urban scene perception and reconstruction. UrbanScene3D contains over 128k high-resolution images covering 16 scenes including large-scale real urban regions and synthetic cities with 136 km^2 area in total. The dataset also contains high-precision LiDAR scans and hundreds of image sets with different observation patterns, which provide a comprehensive benchmark to design and evaluate aerial path planning and 3D reconstruction algorithms. In addition, the dataset, which is built on Unreal Engine and Airsim simulator together "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2107.04286","kind":"arxiv","version":3},"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/2107.04286/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":"2107.04286","created_at":"2026-07-05T04:41:09.928420+00:00"},{"alias_kind":"arxiv_version","alias_value":"2107.04286v3","created_at":"2026-07-05T04:41:09.928420+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2107.04286","created_at":"2026-07-05T04:41:09.928420+00:00"},{"alias_kind":"pith_short_12","alias_value":"TJ6GHHJEGBKB","created_at":"2026-07-05T04:41:09.928420+00:00"},{"alias_kind":"pith_short_16","alias_value":"TJ6GHHJEGBKB4OWB","created_at":"2026-07-05T04:41:09.928420+00:00"},{"alias_kind":"pith_short_8","alias_value":"TJ6GHHJE","created_at":"2026-07-05T04:41:09.928420+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/TJ6GHHJEGBKB4OWBLUEVTF2W4K","json":"https://pith.science/pith/TJ6GHHJEGBKB4OWBLUEVTF2W4K.json","graph_json":"https://pith.science/api/pith-number/TJ6GHHJEGBKB4OWBLUEVTF2W4K/graph.json","events_json":"https://pith.science/api/pith-number/TJ6GHHJEGBKB4OWBLUEVTF2W4K/events.json","paper":"https://pith.science/paper/TJ6GHHJE"},"agent_actions":{"view_html":"https://pith.science/pith/TJ6GHHJEGBKB4OWBLUEVTF2W4K","download_json":"https://pith.science/pith/TJ6GHHJEGBKB4OWBLUEVTF2W4K.json","view_paper":"https://pith.science/paper/TJ6GHHJE","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2107.04286&json=true","fetch_graph":"https://pith.science/api/pith-number/TJ6GHHJEGBKB4OWBLUEVTF2W4K/graph.json","fetch_events":"https://pith.science/api/pith-number/TJ6GHHJEGBKB4OWBLUEVTF2W4K/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/TJ6GHHJEGBKB4OWBLUEVTF2W4K/action/timestamp_anchor","attest_storage":"https://pith.science/pith/TJ6GHHJEGBKB4OWBLUEVTF2W4K/action/storage_attestation","attest_author":"https://pith.science/pith/TJ6GHHJEGBKB4OWBLUEVTF2W4K/action/author_attestation","sign_citation":"https://pith.science/pith/TJ6GHHJEGBKB4OWBLUEVTF2W4K/action/citation_signature","submit_replication":"https://pith.science/pith/TJ6GHHJEGBKB4OWBLUEVTF2W4K/action/replication_record"}},"created_at":"2026-07-05T04:41:09.928420+00:00","updated_at":"2026-07-05T04:41:09.928420+00:00"}