{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:DFZN7UWABNI3WTJJAY73M4D2PQ","short_pith_number":"pith:DFZN7UWA","schema_version":"1.0","canonical_sha256":"1972dfd2c00b51bb4d29063fb6707a7c1d2ea38167a5d6dfc07130bba2d8ee9c","source":{"kind":"arxiv","id":"2207.02202","version":2},"attestation_state":"computed","paper":{"title":"CoBEVT: Cooperative Bird's Eye View Semantic Segmentation with Sparse Transformers","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bolei Zhou, Hao Xiang, Jiaqi Ma, Runsheng Xu, Wei Shao, Zhengzhong Tu","submitted_at":"2022-07-05T17:59:28Z","abstract_excerpt":"Bird's eye view (BEV) semantic segmentation plays a crucial role in spatial sensing for autonomous driving. Although recent literature has made significant progress on BEV map understanding, they are all based on single-agent camera-based systems. These solutions sometimes have difficulty handling occlusions or detecting distant objects in complex traffic scenes. Vehicle-to-Vehicle (V2V) communication technologies have enabled autonomous vehicles to share sensing information, dramatically improving the perception performance and range compared to single-agent systems. In this paper, we propose"},"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":"2207.02202","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2022-07-05T17:59:28Z","cross_cats_sorted":[],"title_canon_sha256":"06c32b9c7a15ffba9298ca7eb4155d17aa1f6362a6185f48adebbec5c28ab4c9","abstract_canon_sha256":"fb59ffc808e54d97a2dbcef86b6848ef9e8f1a6e4c8dd86ae8adb712aec8a7e8"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:00:44.032036Z","signature_b64":"tlmvSsF49LMtpVeT+NcvleqfDTyb6mAcf5fg9e9JCb9MC1r5ZoVqX1z4MPHJ36xVBpyJmwIr39DxjCj3CtnbCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1972dfd2c00b51bb4d29063fb6707a7c1d2ea38167a5d6dfc07130bba2d8ee9c","last_reissued_at":"2026-07-05T05:00:44.031591Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:00:44.031591Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"CoBEVT: Cooperative Bird's Eye View Semantic Segmentation with Sparse Transformers","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bolei Zhou, Hao Xiang, Jiaqi Ma, Runsheng Xu, Wei Shao, Zhengzhong Tu","submitted_at":"2022-07-05T17:59:28Z","abstract_excerpt":"Bird's eye view (BEV) semantic segmentation plays a crucial role in spatial sensing for autonomous driving. Although recent literature has made significant progress on BEV map understanding, they are all based on single-agent camera-based systems. These solutions sometimes have difficulty handling occlusions or detecting distant objects in complex traffic scenes. Vehicle-to-Vehicle (V2V) communication technologies have enabled autonomous vehicles to share sensing information, dramatically improving the perception performance and range compared to single-agent systems. In this paper, we propose"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.02202","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/2207.02202/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":"2207.02202","created_at":"2026-07-05T05:00:44.031648+00:00"},{"alias_kind":"arxiv_version","alias_value":"2207.02202v2","created_at":"2026-07-05T05:00:44.031648+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.02202","created_at":"2026-07-05T05:00:44.031648+00:00"},{"alias_kind":"pith_short_12","alias_value":"DFZN7UWABNI3","created_at":"2026-07-05T05:00:44.031648+00:00"},{"alias_kind":"pith_short_16","alias_value":"DFZN7UWABNI3WTJJ","created_at":"2026-07-05T05:00:44.031648+00:00"},{"alias_kind":"pith_short_8","alias_value":"DFZN7UWA","created_at":"2026-07-05T05:00:44.031648+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":5,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2607.01928","citing_title":"Sparse-Aware Vector Quantization for Bandwidth-Efficient Collaborative 3D Semantic Occupancy Prediction","ref_index":38,"is_internal_anchor":false},{"citing_arxiv_id":"2212.11538","citing_title":"SHLE: Devices Tracking and Depth Filtering for Stereo-based Height Limit Estimation","ref_index":56,"is_internal_anchor":false},{"citing_arxiv_id":"2605.10904","citing_title":"MDrive: Benchmarking Closed-Loop Cooperative Driving for End-to-End Multi-agent Systems","ref_index":76,"is_internal_anchor":false},{"citing_arxiv_id":"2605.01301","citing_title":"From Stealthy Data Fabrication to Unsafe Driving: Realistic Scenario Attacks on Collaborative Perception","ref_index":53,"is_internal_anchor":false},{"citing_arxiv_id":"2604.14454","citing_title":"CooperDrive: Enhancing Driving Decisions Through Cooperative Perception","ref_index":4,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/DFZN7UWABNI3WTJJAY73M4D2PQ","json":"https://pith.science/pith/DFZN7UWABNI3WTJJAY73M4D2PQ.json","graph_json":"https://pith.science/api/pith-number/DFZN7UWABNI3WTJJAY73M4D2PQ/graph.json","events_json":"https://pith.science/api/pith-number/DFZN7UWABNI3WTJJAY73M4D2PQ/events.json","paper":"https://pith.science/paper/DFZN7UWA"},"agent_actions":{"view_html":"https://pith.science/pith/DFZN7UWABNI3WTJJAY73M4D2PQ","download_json":"https://pith.science/pith/DFZN7UWABNI3WTJJAY73M4D2PQ.json","view_paper":"https://pith.science/paper/DFZN7UWA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2207.02202&json=true","fetch_graph":"https://pith.science/api/pith-number/DFZN7UWABNI3WTJJAY73M4D2PQ/graph.json","fetch_events":"https://pith.science/api/pith-number/DFZN7UWABNI3WTJJAY73M4D2PQ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/DFZN7UWABNI3WTJJAY73M4D2PQ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/DFZN7UWABNI3WTJJAY73M4D2PQ/action/storage_attestation","attest_author":"https://pith.science/pith/DFZN7UWABNI3WTJJAY73M4D2PQ/action/author_attestation","sign_citation":"https://pith.science/pith/DFZN7UWABNI3WTJJAY73M4D2PQ/action/citation_signature","submit_replication":"https://pith.science/pith/DFZN7UWABNI3WTJJAY73M4D2PQ/action/replication_record"}},"created_at":"2026-07-05T05:00:44.031648+00:00","updated_at":"2026-07-05T05:00:44.031648+00:00"}