{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:JL2F5YNQR5OVDZFHJNRGYT4MVJ","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":"49f0f3f5627d638a7d350d144d47cf635ba0239a6945f7a8be39b28cdccaf831","cross_cats_sorted":["cs.AR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-02-13T17:39:28Z","title_canon_sha256":"716d707a9e5d75570d006c8e354d24c1c0c1a0f30a5a36c9ca612a4aa28b2a9f"},"schema_version":"1.0","source":{"id":"2502.09528","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.09528","created_at":"2026-07-05T10:13:58Z"},{"alias_kind":"arxiv_version","alias_value":"2502.09528v1","created_at":"2026-07-05T10:13:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.09528","created_at":"2026-07-05T10:13:58Z"},{"alias_kind":"pith_short_12","alias_value":"JL2F5YNQR5OV","created_at":"2026-07-05T10:13:58Z"},{"alias_kind":"pith_short_16","alias_value":"JL2F5YNQR5OVDZFH","created_at":"2026-07-05T10:13:58Z"},{"alias_kind":"pith_short_8","alias_value":"JL2F5YNQ","created_at":"2026-07-05T10:13:58Z"}],"graph_snapshots":[{"event_id":"sha256:70e50fd1f61a86179cdb761fd46ad1df43aa72454d40b2e6d0b49f4258449c4c","target":"graph","created_at":"2026-07-05T10:13:58Z","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/2502.09528/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Machine learning algorithms have enabled high quality stereo depth estimation to run on Augmented and Virtual Reality (AR/VR) devices. However, high energy consumption across the full image processing stack prevents stereo depth algorithms from running effectively on battery-limited devices. This paper introduces SteROI-D, a full stereo depth system paired with a mapping methodology. SteROI-D exploits Region-of-Interest (ROI) and temporal sparsity at the system level to save energy. SteROI-D's flexible and heterogeneous compute fabric supports diverse ROIs. Importantly, we introduce a systemat","authors_text":"Andrew Berkovich, Jack Erhardt, Reid Pinkham, Zhengya Zhang, Ziang Li","cross_cats":["cs.AR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-02-13T17:39:28Z","title":"SteROI-D: System Design and Mapping for Stereo Depth Inference on Regions of Interest"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.09528","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":"sha256:1a395adc0f9802d01a9ac07e15e12e8cd56d29336f20722cddf9c9a8e4026617","target":"record","created_at":"2026-07-05T10:13:58Z","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":"49f0f3f5627d638a7d350d144d47cf635ba0239a6945f7a8be39b28cdccaf831","cross_cats_sorted":["cs.AR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-02-13T17:39:28Z","title_canon_sha256":"716d707a9e5d75570d006c8e354d24c1c0c1a0f30a5a36c9ca612a4aa28b2a9f"},"schema_version":"1.0","source":{"id":"2502.09528","kind":"arxiv","version":1}},"canonical_sha256":"4af45ee1b08f5d51e4a74b626c4f8caa612ef46be5e300739d0c676ce9fdfd8b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4af45ee1b08f5d51e4a74b626c4f8caa612ef46be5e300739d0c676ce9fdfd8b","first_computed_at":"2026-07-05T10:13:58.979587Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:13:58.979587Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Y5VL+PuN3YFvMzGfb8+K4TKesodMlwOO7SlaAnVVjOX62ByJbwZDebfEwWW+kuRTpsKDyGxDrMhilzLGYioeAg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:13:58.980050Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.09528","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1a395adc0f9802d01a9ac07e15e12e8cd56d29336f20722cddf9c9a8e4026617","sha256:70e50fd1f61a86179cdb761fd46ad1df43aa72454d40b2e6d0b49f4258449c4c"],"state_sha256":"773f29e74af7a50f806eb3056f46990191229330dfcf0d774c029888b7d23512"}