{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:WH256MJ6VADY5Y7TPWBOAWQW4T","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":"64b3f35ded98caaf131e7d538d80442023a101cf12f939f1b80db6450b5e8cc5","cross_cats_sorted":["cs.RO","eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-08-14T12:35:39Z","title_canon_sha256":"a9fede363043ebc460f70b77f1387ef9db48f07dac9928f791b3f643dd4ff0d5"},"schema_version":"1.0","source":{"id":"2308.07104","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.07104","created_at":"2026-07-05T06:53:09Z"},{"alias_kind":"arxiv_version","alias_value":"2308.07104v2","created_at":"2026-07-05T06:53:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.07104","created_at":"2026-07-05T06:53:09Z"},{"alias_kind":"pith_short_12","alias_value":"WH256MJ6VADY","created_at":"2026-07-05T06:53:09Z"},{"alias_kind":"pith_short_16","alias_value":"WH256MJ6VADY5Y7T","created_at":"2026-07-05T06:53:09Z"},{"alias_kind":"pith_short_8","alias_value":"WH256MJ6","created_at":"2026-07-05T06:53:09Z"}],"graph_snapshots":[{"event_id":"sha256:146f3d3fc22a20db4f301fb0d88c76b1aa7f8ed538e21f8c3450db2ffc808046","target":"graph","created_at":"2026-07-05T06:53:09Z","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/2308.07104/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Key-point-based scene understanding is fundamental for autonomous driving applications. At the same time, optical flow plays an important role in many vision tasks. However, due to the implicit bias of equal attention on all points, classic data-driven optical flow estimation methods yield less satisfactory performance on key points, limiting their implementations in key-point-critical safety-relevant scenarios. To address these issues, we introduce a points-based modeling method that requires the model to learn key-point-related priors explicitly. Based on the modeling method, we present Focu","authors_text":"Hao Shi, Huajian Ni, Kailun Yang, Kaiwei Wang, Qi Jiang, Yaozu Ye, Ze Wang, Zhonghua Yi","cross_cats":["cs.RO","eess.IV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-08-14T12:35:39Z","title":"FocusFlow: Boosting Key-Points Optical Flow Estimation for Autonomous Driving"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.07104","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":"sha256:93b2ecb3fe16b59edcd59886ff73b6d591c61163d0b640415b47fd971c9f6839","target":"record","created_at":"2026-07-05T06:53:09Z","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":"64b3f35ded98caaf131e7d538d80442023a101cf12f939f1b80db6450b5e8cc5","cross_cats_sorted":["cs.RO","eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-08-14T12:35:39Z","title_canon_sha256":"a9fede363043ebc460f70b77f1387ef9db48f07dac9928f791b3f643dd4ff0d5"},"schema_version":"1.0","source":{"id":"2308.07104","kind":"arxiv","version":2}},"canonical_sha256":"b1f5df313ea8078ee3f37d82e05a16e4c2dfc92a2a5289e0556010429adce5f3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b1f5df313ea8078ee3f37d82e05a16e4c2dfc92a2a5289e0556010429adce5f3","first_computed_at":"2026-07-05T06:53:09.219871Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:53:09.219871Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"igEFxFZKZMIAQQOozcUBmMK0UActjLVlyr8J5Kgm8ksSFM1kwHvcKpsmsYg2bX14F6ZBQBf/+ZloNZWb1NwYBw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:53:09.220258Z","signed_message":"canonical_sha256_bytes"},"source_id":"2308.07104","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:93b2ecb3fe16b59edcd59886ff73b6d591c61163d0b640415b47fd971c9f6839","sha256:146f3d3fc22a20db4f301fb0d88c76b1aa7f8ed538e21f8c3450db2ffc808046"],"state_sha256":"dc58d47c14a2dd1d3bb522cddc54a554f18522e620db6b78db989cb729217c2b"}