{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:4ODFYGM3YPO5ZFFZUYENFMMMDN","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":"709b7e4549666f8c545a195069e67fedae4b3f4b5da62f2ebeef0704164ab2d5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-09T13:28:52Z","title_canon_sha256":"61c450e92cb2955dfe7cccc01323c41db2774d9ece14c21a0da3b9f08994c651"},"schema_version":"1.0","source":{"id":"1805.03511","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.03511","created_at":"2026-05-18T00:16:13Z"},{"alias_kind":"arxiv_version","alias_value":"1805.03511v2","created_at":"2026-05-18T00:16:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.03511","created_at":"2026-05-18T00:16:13Z"},{"alias_kind":"pith_short_12","alias_value":"4ODFYGM3YPO5","created_at":"2026-05-18T12:32:05Z"},{"alias_kind":"pith_short_16","alias_value":"4ODFYGM3YPO5ZFFZ","created_at":"2026-05-18T12:32:05Z"},{"alias_kind":"pith_short_8","alias_value":"4ODFYGM3","created_at":"2026-05-18T12:32:05Z"}],"graph_snapshots":[{"event_id":"sha256:b6044c4316ed02648b6de53bf41aa4d48ef11b1ee419f2b74af94cd5686b256a","target":"graph","created_at":"2026-05-18T00:16:13Z","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"},"paper":{"abstract_excerpt":"Automated toll systems rely on proper classification of the passing vehicles. This is especially difficult when the images used for classification only cover parts of the vehicle. To obtain information about the whole vehicle. we reconstruct the vehicle as 3D object and exploit this additional information within a Convolutional Neural Network (CNN). However, when using deep networks for 3D object classification, large amounts of dense 3D models are required for good accuracy, which are often neither available nor feasible to process due to memory requirements. Therefore, in our method we repro","authors_text":"Friedrich Fraundorfer, Georg Waltner, Horst Bischof, Horst Possegger, Michael Maurer, Michael Opitz, Patrick Ruprecht, Thomas Holzmann","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-09T13:28:52Z","title":"Deep 2.5D Vehicle Classification with Sparse SfM Depth Prior for Automated Toll Systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.03511","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":"sha256:2928cbd52b09435f798ed3ec751858fc984a0970675cd82dfc6070fdd43d4f32","target":"record","created_at":"2026-05-18T00:16:13Z","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":"709b7e4549666f8c545a195069e67fedae4b3f4b5da62f2ebeef0704164ab2d5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-09T13:28:52Z","title_canon_sha256":"61c450e92cb2955dfe7cccc01323c41db2774d9ece14c21a0da3b9f08994c651"},"schema_version":"1.0","source":{"id":"1805.03511","kind":"arxiv","version":2}},"canonical_sha256":"e3865c199bc3dddc94b9a608d2b18c1b748018555e662137d0faaec4fdadfeb5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e3865c199bc3dddc94b9a608d2b18c1b748018555e662137d0faaec4fdadfeb5","first_computed_at":"2026-05-18T00:16:13.675897Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:16:13.675897Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KdFni056s4OGfWgEIdPn2G63B2oYLr/Uoog0nIPiSOQWK3KFJGQdV0uUHMNzUIvtBKHny1aZK8ysoCjpGHX8Dw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:16:13.676832Z","signed_message":"canonical_sha256_bytes"},"source_id":"1805.03511","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2928cbd52b09435f798ed3ec751858fc984a0970675cd82dfc6070fdd43d4f32","sha256:b6044c4316ed02648b6de53bf41aa4d48ef11b1ee419f2b74af94cd5686b256a"],"state_sha256":"f7c01451772b8bcdec32c15d603896b37874d2e811c2cde34eb6da8d9e0f5cfd"}