{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:BNVF6K3EHLXJYBWZQZLF5TIJPW","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":"735737d3b244e56efca2e8945cdb0ff6b079234c49fb2c728a5b31502a46cad4","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-02-19T11:56:44Z","title_canon_sha256":"5bc6c8becab344adb2a3b3ec4ac459f9a00800425febf0220eb6d45dab405b19"},"schema_version":"1.0","source":{"id":"2102.09883","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2102.09883","created_at":"2026-07-05T02:16:31Z"},{"alias_kind":"arxiv_version","alias_value":"2102.09883v1","created_at":"2026-07-05T02:16:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2102.09883","created_at":"2026-07-05T02:16:31Z"},{"alias_kind":"pith_short_12","alias_value":"BNVF6K3EHLXJ","created_at":"2026-07-05T02:16:31Z"},{"alias_kind":"pith_short_16","alias_value":"BNVF6K3EHLXJYBWZ","created_at":"2026-07-05T02:16:31Z"},{"alias_kind":"pith_short_8","alias_value":"BNVF6K3E","created_at":"2026-07-05T02:16:31Z"}],"graph_snapshots":[{"event_id":"sha256:b74d006ad3dc285c811889e50a8b9a9eb53d844d1a2093f55150fd89bc1605fd","target":"graph","created_at":"2026-07-05T02:16:31Z","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/2102.09883/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Predicting future 3D LiDAR pointclouds is a challenging task that is useful in many applications in autonomous driving such as trajectory prediction, pose forecasting and decision making. In this work, we propose a new LiDAR prediction framework that is based on generative models namely Variational Recurrent Neural Networks (VRNNs), titled Stochastic LiDAR Prediction and Completion (SLPC). Our algorithm is able to address the limitations of previous video prediction frameworks when dealing with sparse data by spatially inpainting the depth maps in the upcoming frames. Our contributions can thu","authors_text":"Alexander Braun, Bin Yang, George Eskandar, Karim Armanious, Martin Meinke","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-02-19T11:56:44Z","title":"SLPC: a VRNN-based approach for stochastic lidar prediction and completion in autonomous driving"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2102.09883","kind":"arxiv","version":1},"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:aeacbec64eda6c2d38c397e0af3a8c569309ea68e98045453d0f5993156c8d63","target":"record","created_at":"2026-07-05T02:16:31Z","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":"735737d3b244e56efca2e8945cdb0ff6b079234c49fb2c728a5b31502a46cad4","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-02-19T11:56:44Z","title_canon_sha256":"5bc6c8becab344adb2a3b3ec4ac459f9a00800425febf0220eb6d45dab405b19"},"schema_version":"1.0","source":{"id":"2102.09883","kind":"arxiv","version":1}},"canonical_sha256":"0b6a5f2b643aee9c06d986565ecd097db5359a612df836943bfcdbed1bd7045f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0b6a5f2b643aee9c06d986565ecd097db5359a612df836943bfcdbed1bd7045f","first_computed_at":"2026-07-05T02:16:31.963582Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:16:31.963582Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FqbnwnQ7cnC4OqMIkmSbr6HFhCLaxtEoQZC4+oYPcRaqFQSx5znaLfe6u4BsMduuxge/PDZoWCyg/2nHK9+5Bw==","signature_status":"signed_v1","signed_at":"2026-07-05T02:16:31.963995Z","signed_message":"canonical_sha256_bytes"},"source_id":"2102.09883","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:aeacbec64eda6c2d38c397e0af3a8c569309ea68e98045453d0f5993156c8d63","sha256:b74d006ad3dc285c811889e50a8b9a9eb53d844d1a2093f55150fd89bc1605fd"],"state_sha256":"41441848011439e54cfd9b84ae560d95dffea232447354b0a205c959daccf7ff"}