{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:N2HVFRE7CSMBOBYNDWLNAFEQXV","short_pith_number":"pith:N2HVFRE7","canonical_record":{"source":{"id":"2402.17351","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-02-27T09:41:59Z","cross_cats_sorted":[],"title_canon_sha256":"6763bbb157c7aa4da6577cce726bd2be304f58f9f9921ad95f16b3e9e20c0dea","abstract_canon_sha256":"51fcd7b86c5e217c2bf5fbc60f1cd9aa98310e41a68850a7d0932ade58c31d4a"},"schema_version":"1.0"},"canonical_sha256":"6e8f52c49f149817070d1d96d01490bd5bf9c2ccbf153a456366d9aaa672b39d","source":{"kind":"arxiv","id":"2402.17351","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.17351","created_at":"2026-07-05T07:58:47Z"},{"alias_kind":"arxiv_version","alias_value":"2402.17351v2","created_at":"2026-07-05T07:58:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.17351","created_at":"2026-07-05T07:58:47Z"},{"alias_kind":"pith_short_12","alias_value":"N2HVFRE7CSMB","created_at":"2026-07-05T07:58:47Z"},{"alias_kind":"pith_short_16","alias_value":"N2HVFRE7CSMBOBYN","created_at":"2026-07-05T07:58:47Z"},{"alias_kind":"pith_short_8","alias_value":"N2HVFRE7","created_at":"2026-07-05T07:58:47Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:N2HVFRE7CSMBOBYNDWLNAFEQXV","target":"record","payload":{"canonical_record":{"source":{"id":"2402.17351","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-02-27T09:41:59Z","cross_cats_sorted":[],"title_canon_sha256":"6763bbb157c7aa4da6577cce726bd2be304f58f9f9921ad95f16b3e9e20c0dea","abstract_canon_sha256":"51fcd7b86c5e217c2bf5fbc60f1cd9aa98310e41a68850a7d0932ade58c31d4a"},"schema_version":"1.0"},"canonical_sha256":"6e8f52c49f149817070d1d96d01490bd5bf9c2ccbf153a456366d9aaa672b39d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:58:47.081601Z","signature_b64":"+10yKcqlnG2RXidAJyC5WQl+1VIaTE89CWeCAnPZGzzESK7+ZyI0CNxJ39ax5EdkxuwDuHMXI3o69zQOZ83oAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6e8f52c49f149817070d1d96d01490bd5bf9c2ccbf153a456366d9aaa672b39d","last_reissued_at":"2026-07-05T07:58:47.081057Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:58:47.081057Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.17351","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:58:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TPd4l5RYEBb2QFv91VFfO5/lIXmmFjxJhqUve8Ukzv/EX9GmRyuhEH/EiKw17tguFDefOLzxKann8cRftL9XBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T20:39:30.709784Z"},"content_sha256":"bb214e3bc7b9b2ff3781149872deaa4aa08c6a0c402f11ee5bb66a87794cdecc","schema_version":"1.0","event_id":"sha256:bb214e3bc7b9b2ff3781149872deaa4aa08c6a0c402f11ee5bb66a87794cdecc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:N2HVFRE7CSMBOBYNDWLNAFEQXV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ICP-Flow: LiDAR Scene Flow Estimation with ICP","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Holger Caesar, Yancong Lin","submitted_at":"2024-02-27T09:41:59Z","abstract_excerpt":"Scene flow characterizes the 3D motion between two LiDAR scans captured by an autonomous vehicle at nearby timesteps. Prevalent methods consider scene flow as point-wise unconstrained flow vectors that can be learned by either large-scale training beforehand or time-consuming optimization at inference. However, these methods do not take into account that objects in autonomous driving often move rigidly. We incorporate this rigid-motion assumption into our design, where the goal is to associate objects over scans and then estimate the locally rigid transformations. We propose ICP-Flow, a learni"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.17351","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/2402.17351/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":"2026-07-05T07:58:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6WaZsqCXVMrsieyG9EjlNMuNyz8lwLdfVmaboJr88pIpqkp/+/kzk4maMl2eBFpLF8Da+qsgYkg0mp0MZPV1CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T20:39:30.710168Z"},"content_sha256":"dcf548d299689191edd45cdcd19707f7b3590e1e50df170e7e24f3811854d54c","schema_version":"1.0","event_id":"sha256:dcf548d299689191edd45cdcd19707f7b3590e1e50df170e7e24f3811854d54c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/N2HVFRE7CSMBOBYNDWLNAFEQXV/bundle.json","state_url":"https://pith.science/pith/N2HVFRE7CSMBOBYNDWLNAFEQXV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/N2HVFRE7CSMBOBYNDWLNAFEQXV/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":"2026-08-05T20:39:30Z","links":{"resolver":"https://pith.science/pith/N2HVFRE7CSMBOBYNDWLNAFEQXV","bundle":"https://pith.science/pith/N2HVFRE7CSMBOBYNDWLNAFEQXV/bundle.json","state":"https://pith.science/pith/N2HVFRE7CSMBOBYNDWLNAFEQXV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/N2HVFRE7CSMBOBYNDWLNAFEQXV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:N2HVFRE7CSMBOBYNDWLNAFEQXV","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":"51fcd7b86c5e217c2bf5fbc60f1cd9aa98310e41a68850a7d0932ade58c31d4a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-02-27T09:41:59Z","title_canon_sha256":"6763bbb157c7aa4da6577cce726bd2be304f58f9f9921ad95f16b3e9e20c0dea"},"schema_version":"1.0","source":{"id":"2402.17351","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.17351","created_at":"2026-07-05T07:58:47Z"},{"alias_kind":"arxiv_version","alias_value":"2402.17351v2","created_at":"2026-07-05T07:58:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.17351","created_at":"2026-07-05T07:58:47Z"},{"alias_kind":"pith_short_12","alias_value":"N2HVFRE7CSMB","created_at":"2026-07-05T07:58:47Z"},{"alias_kind":"pith_short_16","alias_value":"N2HVFRE7CSMBOBYN","created_at":"2026-07-05T07:58:47Z"},{"alias_kind":"pith_short_8","alias_value":"N2HVFRE7","created_at":"2026-07-05T07:58:47Z"}],"graph_snapshots":[{"event_id":"sha256:dcf548d299689191edd45cdcd19707f7b3590e1e50df170e7e24f3811854d54c","target":"graph","created_at":"2026-07-05T07:58:47Z","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/2402.17351/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Scene flow characterizes the 3D motion between two LiDAR scans captured by an autonomous vehicle at nearby timesteps. Prevalent methods consider scene flow as point-wise unconstrained flow vectors that can be learned by either large-scale training beforehand or time-consuming optimization at inference. However, these methods do not take into account that objects in autonomous driving often move rigidly. We incorporate this rigid-motion assumption into our design, where the goal is to associate objects over scans and then estimate the locally rigid transformations. We propose ICP-Flow, a learni","authors_text":"Holger Caesar, Yancong Lin","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-02-27T09:41:59Z","title":"ICP-Flow: LiDAR Scene Flow Estimation with ICP"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.17351","kind":"arxiv","version":2},"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:bb214e3bc7b9b2ff3781149872deaa4aa08c6a0c402f11ee5bb66a87794cdecc","target":"record","created_at":"2026-07-05T07:58:47Z","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":"51fcd7b86c5e217c2bf5fbc60f1cd9aa98310e41a68850a7d0932ade58c31d4a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-02-27T09:41:59Z","title_canon_sha256":"6763bbb157c7aa4da6577cce726bd2be304f58f9f9921ad95f16b3e9e20c0dea"},"schema_version":"1.0","source":{"id":"2402.17351","kind":"arxiv","version":2}},"canonical_sha256":"6e8f52c49f149817070d1d96d01490bd5bf9c2ccbf153a456366d9aaa672b39d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6e8f52c49f149817070d1d96d01490bd5bf9c2ccbf153a456366d9aaa672b39d","first_computed_at":"2026-07-05T07:58:47.081057Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:58:47.081057Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+10yKcqlnG2RXidAJyC5WQl+1VIaTE89CWeCAnPZGzzESK7+ZyI0CNxJ39ax5EdkxuwDuHMXI3o69zQOZ83oAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:58:47.081601Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.17351","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bb214e3bc7b9b2ff3781149872deaa4aa08c6a0c402f11ee5bb66a87794cdecc","sha256:dcf548d299689191edd45cdcd19707f7b3590e1e50df170e7e24f3811854d54c"],"state_sha256":"4c5528cdde18cbe91daf2f5809fe657dba6d5c91a43a96d07d9f8a1dc4dbf618"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"k4yOd9EAJJke+tgiAcrAAzy9K9iC4/QuqBr7xrQxs6rTJQjRiTPotAWU+O6QsrRhyrSOFpKnDmQSCnEQ9Is3AA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T20:39:30.712921Z","bundle_sha256":"da4306eb2367c8d776689d680679e873634c0fba413e872c7281ff5d1e3bcc74"}}