{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:RYCNIYHDKTCMQE2JSBTQMM55SA","short_pith_number":"pith:RYCNIYHD","schema_version":"1.0","canonical_sha256":"8e04d460e354c4c8134990670633bd902ce6c84a386b727adb329bfb7ceaebae","source":{"kind":"arxiv","id":"2312.13081","version":1},"attestation_state":"computed","paper":{"title":"BEVSeg2TP: Surround View Camera Bird's-Eye-View Based Joint Vehicle Segmentation and Ego Vehicle Trajectory Prediction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Arindam Das, Ciar\\'an Eising, Ganesh Sistu, Mark Halton, Sushil Sharma","submitted_at":"2023-12-20T15:02:37Z","abstract_excerpt":"Trajectory prediction is, naturally, a key task for vehicle autonomy. While the number of traffic rules is limited, the combinations and uncertainties associated with each agent's behaviour in real-world scenarios are nearly impossible to encode. Consequently, there is a growing interest in learning-based trajectory prediction. The proposed method in this paper predicts trajectories by considering perception and trajectory prediction as a unified system. In considering them as unified tasks, we show that there is the potential to improve the performance of perception. To achieve these goals, w"},"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":"2312.13081","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-20T15:02:37Z","cross_cats_sorted":[],"title_canon_sha256":"5b5dd6995315232d3271de9e7e30b2589c32156de9973a855c1132dd4c823247","abstract_canon_sha256":"11e44697526f59c1241807836e74e674ce5e5112618838ba4c0245d6fefe7f7d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:26:32.089803Z","signature_b64":"bkCNO8cEqKUQvT02HjXJg47ocCSOQACm8hGZ8UHwr1ar2FFOsdw8ZieuVJMOuTjkYCNHw3o7KN6Xoe6NflpqAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8e04d460e354c4c8134990670633bd902ce6c84a386b727adb329bfb7ceaebae","last_reissued_at":"2026-07-05T07:26:32.089362Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:26:32.089362Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"BEVSeg2TP: Surround View Camera Bird's-Eye-View Based Joint Vehicle Segmentation and Ego Vehicle Trajectory Prediction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Arindam Das, Ciar\\'an Eising, Ganesh Sistu, Mark Halton, Sushil Sharma","submitted_at":"2023-12-20T15:02:37Z","abstract_excerpt":"Trajectory prediction is, naturally, a key task for vehicle autonomy. While the number of traffic rules is limited, the combinations and uncertainties associated with each agent's behaviour in real-world scenarios are nearly impossible to encode. Consequently, there is a growing interest in learning-based trajectory prediction. The proposed method in this paper predicts trajectories by considering perception and trajectory prediction as a unified system. In considering them as unified tasks, we show that there is the potential to improve the performance of perception. To achieve these goals, w"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.13081","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/2312.13081/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":"2312.13081","created_at":"2026-07-05T07:26:32.089419+00:00"},{"alias_kind":"arxiv_version","alias_value":"2312.13081v1","created_at":"2026-07-05T07:26:32.089419+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.13081","created_at":"2026-07-05T07:26:32.089419+00:00"},{"alias_kind":"pith_short_12","alias_value":"RYCNIYHDKTCM","created_at":"2026-07-05T07:26:32.089419+00:00"},{"alias_kind":"pith_short_16","alias_value":"RYCNIYHDKTCMQE2J","created_at":"2026-07-05T07:26:32.089419+00:00"},{"alias_kind":"pith_short_8","alias_value":"RYCNIYHD","created_at":"2026-07-05T07:26:32.089419+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/RYCNIYHDKTCMQE2JSBTQMM55SA","json":"https://pith.science/pith/RYCNIYHDKTCMQE2JSBTQMM55SA.json","graph_json":"https://pith.science/api/pith-number/RYCNIYHDKTCMQE2JSBTQMM55SA/graph.json","events_json":"https://pith.science/api/pith-number/RYCNIYHDKTCMQE2JSBTQMM55SA/events.json","paper":"https://pith.science/paper/RYCNIYHD"},"agent_actions":{"view_html":"https://pith.science/pith/RYCNIYHDKTCMQE2JSBTQMM55SA","download_json":"https://pith.science/pith/RYCNIYHDKTCMQE2JSBTQMM55SA.json","view_paper":"https://pith.science/paper/RYCNIYHD","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2312.13081&json=true","fetch_graph":"https://pith.science/api/pith-number/RYCNIYHDKTCMQE2JSBTQMM55SA/graph.json","fetch_events":"https://pith.science/api/pith-number/RYCNIYHDKTCMQE2JSBTQMM55SA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RYCNIYHDKTCMQE2JSBTQMM55SA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RYCNIYHDKTCMQE2JSBTQMM55SA/action/storage_attestation","attest_author":"https://pith.science/pith/RYCNIYHDKTCMQE2JSBTQMM55SA/action/author_attestation","sign_citation":"https://pith.science/pith/RYCNIYHDKTCMQE2JSBTQMM55SA/action/citation_signature","submit_replication":"https://pith.science/pith/RYCNIYHDKTCMQE2JSBTQMM55SA/action/replication_record"}},"created_at":"2026-07-05T07:26:32.089419+00:00","updated_at":"2026-07-05T07:26:32.089419+00:00"}