{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:AU4FELAP5Y6OJXBWYMGK2PHNYE","short_pith_number":"pith:AU4FELAP","canonical_record":{"source":{"id":"2206.01256","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-06-02T19:13:03Z","cross_cats_sorted":[],"title_canon_sha256":"81680ce8322183b0f165f422a542515c90d3bd2c4df4fa2cc611d47e2dab7802","abstract_canon_sha256":"b7ead5a67f604678c05c9bf4b712037e32de0798681413941be129ecd8ebab21"},"schema_version":"1.0"},"canonical_sha256":"0538522c0fee3ce4dc36c30cad3cedc12c26bef18fd7c453ed1078d35ab64630","source":{"kind":"arxiv","id":"2206.01256","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2206.01256","created_at":"2026-07-05T05:15:40Z"},{"alias_kind":"arxiv_version","alias_value":"2206.01256v3","created_at":"2026-07-05T05:15:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.01256","created_at":"2026-07-05T05:15:40Z"},{"alias_kind":"pith_short_12","alias_value":"AU4FELAP5Y6O","created_at":"2026-07-05T05:15:40Z"},{"alias_kind":"pith_short_16","alias_value":"AU4FELAP5Y6OJXBW","created_at":"2026-07-05T05:15:40Z"},{"alias_kind":"pith_short_8","alias_value":"AU4FELAP","created_at":"2026-07-05T05:15:40Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:AU4FELAP5Y6OJXBWYMGK2PHNYE","target":"record","payload":{"canonical_record":{"source":{"id":"2206.01256","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-06-02T19:13:03Z","cross_cats_sorted":[],"title_canon_sha256":"81680ce8322183b0f165f422a542515c90d3bd2c4df4fa2cc611d47e2dab7802","abstract_canon_sha256":"b7ead5a67f604678c05c9bf4b712037e32de0798681413941be129ecd8ebab21"},"schema_version":"1.0"},"canonical_sha256":"0538522c0fee3ce4dc36c30cad3cedc12c26bef18fd7c453ed1078d35ab64630","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:15:40.305748Z","signature_b64":"fLMnNABjX+uCu0of5Ng+Mby5ZtyZQISIsKEC1OFwH7MIUzCbO8UXutlE7iFLZ7ewDpGictW4MIRPY8A1E/osAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0538522c0fee3ce4dc36c30cad3cedc12c26bef18fd7c453ed1078d35ab64630","last_reissued_at":"2026-07-05T05:15:40.305229Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:15:40.305229Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2206.01256","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:15:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MS5gOPu9SB7DRIw2rUt3aJae16gQHM8r9n0fKrgD510xQk4N+loMUVP4txhlRc9PQx0SzujGvYdaj/NyNcwaAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T09:44:49.444714Z"},"content_sha256":"9454c2ea96889e2304edc635899a07007297eb6432f846b99670d373305ddd36","schema_version":"1.0","event_id":"sha256:9454c2ea96889e2304edc635899a07007297eb6432f846b99670d373305ddd36"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:AU4FELAP5Y6OJXBWYMGK2PHNYE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Aqi Gao, Fan Jia, Jian Sun, Junjie Yan, Shuailin Li, Tiancai Wang, Xiangyu Zhang, Yingfei Liu","submitted_at":"2022-06-02T19:13:03Z","abstract_excerpt":"In this paper, we propose PETRv2, a unified framework for 3D perception from multi-view images. Based on PETR, PETRv2 explores the effectiveness of temporal modeling, which utilizes the temporal information of previous frames to boost 3D object detection. More specifically, we extend the 3D position embedding (3D PE) in PETR for temporal modeling. The 3D PE achieves the temporal alignment on object position of different frames. A feature-guided position encoder is further introduced to improve the data adaptability of 3D PE. To support for multi-task learning (e.g., BEV segmentation and 3D lan"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.01256","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/2206.01256/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:15:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BSJCKFVwnt7skLvpGuVKXu0zEv20RBWDdxwK15bgPqSoJFGmw2IhPRJK0e9mYpxL3X9TDhds98DKFH2GUAXQDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T09:44:49.445217Z"},"content_sha256":"02c6cd3450f5d23e84c322705b6254878cda0299e75c9f5493be8d5848bb2dc3","schema_version":"1.0","event_id":"sha256:02c6cd3450f5d23e84c322705b6254878cda0299e75c9f5493be8d5848bb2dc3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AU4FELAP5Y6OJXBWYMGK2PHNYE/bundle.json","state_url":"https://pith.science/pith/AU4FELAP5Y6OJXBWYMGK2PHNYE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AU4FELAP5Y6OJXBWYMGK2PHNYE/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-19T09:44:49Z","links":{"resolver":"https://pith.science/pith/AU4FELAP5Y6OJXBWYMGK2PHNYE","bundle":"https://pith.science/pith/AU4FELAP5Y6OJXBWYMGK2PHNYE/bundle.json","state":"https://pith.science/pith/AU4FELAP5Y6OJXBWYMGK2PHNYE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AU4FELAP5Y6OJXBWYMGK2PHNYE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:AU4FELAP5Y6OJXBWYMGK2PHNYE","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"b7ead5a67f604678c05c9bf4b712037e32de0798681413941be129ecd8ebab21","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-06-02T19:13:03Z","title_canon_sha256":"81680ce8322183b0f165f422a542515c90d3bd2c4df4fa2cc611d47e2dab7802"},"schema_version":"1.0","source":{"id":"2206.01256","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2206.01256","created_at":"2026-07-05T05:15:40Z"},{"alias_kind":"arxiv_version","alias_value":"2206.01256v3","created_at":"2026-07-05T05:15:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.01256","created_at":"2026-07-05T05:15:40Z"},{"alias_kind":"pith_short_12","alias_value":"AU4FELAP5Y6O","created_at":"2026-07-05T05:15:40Z"},{"alias_kind":"pith_short_16","alias_value":"AU4FELAP5Y6OJXBW","created_at":"2026-07-05T05:15:40Z"},{"alias_kind":"pith_short_8","alias_value":"AU4FELAP","created_at":"2026-07-05T05:15:40Z"}],"graph_snapshots":[{"event_id":"sha256:02c6cd3450f5d23e84c322705b6254878cda0299e75c9f5493be8d5848bb2dc3","target":"graph","created_at":"2026-07-05T05:15:40Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2206.01256/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we propose PETRv2, a unified framework for 3D perception from multi-view images. Based on PETR, PETRv2 explores the effectiveness of temporal modeling, which utilizes the temporal information of previous frames to boost 3D object detection. More specifically, we extend the 3D position embedding (3D PE) in PETR for temporal modeling. The 3D PE achieves the temporal alignment on object position of different frames. A feature-guided position encoder is further introduced to improve the data adaptability of 3D PE. To support for multi-task learning (e.g., BEV segmentation and 3D lan","authors_text":"Aqi Gao, Fan Jia, Jian Sun, Junjie Yan, Shuailin Li, Tiancai Wang, Xiangyu Zhang, Yingfei Liu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-06-02T19:13:03Z","title":"PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.01256","kind":"arxiv","version":3},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:9454c2ea96889e2304edc635899a07007297eb6432f846b99670d373305ddd36","target":"record","created_at":"2026-07-05T05:15:40Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"b7ead5a67f604678c05c9bf4b712037e32de0798681413941be129ecd8ebab21","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-06-02T19:13:03Z","title_canon_sha256":"81680ce8322183b0f165f422a542515c90d3bd2c4df4fa2cc611d47e2dab7802"},"schema_version":"1.0","source":{"id":"2206.01256","kind":"arxiv","version":3}},"canonical_sha256":"0538522c0fee3ce4dc36c30cad3cedc12c26bef18fd7c453ed1078d35ab64630","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0538522c0fee3ce4dc36c30cad3cedc12c26bef18fd7c453ed1078d35ab64630","first_computed_at":"2026-07-05T05:15:40.305229Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:15:40.305229Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fLMnNABjX+uCu0of5Ng+Mby5ZtyZQISIsKEC1OFwH7MIUzCbO8UXutlE7iFLZ7ewDpGictW4MIRPY8A1E/osAw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:15:40.305748Z","signed_message":"canonical_sha256_bytes"},"source_id":"2206.01256","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9454c2ea96889e2304edc635899a07007297eb6432f846b99670d373305ddd36","sha256:02c6cd3450f5d23e84c322705b6254878cda0299e75c9f5493be8d5848bb2dc3"],"state_sha256":"a539c657d553bd49d73a550de284f1f8004bca9637ce1802e93b0a50f3df4ff7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SwOL2S1gZJTnbUQTN3fV9LvK0SoWOTh3dHpN9QbqE8U1tzUEZ4AGSe/4gSc1tSXDPny1A0AUSo5gkbGVrsKNCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T09:44:49.449986Z","bundle_sha256":"ab84edf84e0237af86ce8f2f30d693bc4b5ad3cc6c9dd69f2188ca59269ab58e"}}