{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:HWKIOMYJ2GTQ6ZIMT6VGPZGZLT","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":"52a0a60e68280d24f0651e22339f77321b616e95d2bc539ef840fed07c7a7f27","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-06-25T09:37:09Z","title_canon_sha256":"2383b4da6dc289d40ed4263c01d8a8ed5bcc36bc5d6bcfe3eb84d6dda96dde0e"},"schema_version":"1.0","source":{"id":"2406.17414","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.17414","created_at":"2026-07-05T09:30:17Z"},{"alias_kind":"arxiv_version","alias_value":"2406.17414v2","created_at":"2026-07-05T09:30:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.17414","created_at":"2026-07-05T09:30:17Z"},{"alias_kind":"pith_short_12","alias_value":"HWKIOMYJ2GTQ","created_at":"2026-07-05T09:30:17Z"},{"alias_kind":"pith_short_16","alias_value":"HWKIOMYJ2GTQ6ZIM","created_at":"2026-07-05T09:30:17Z"},{"alias_kind":"pith_short_8","alias_value":"HWKIOMYJ","created_at":"2026-07-05T09:30:17Z"}],"graph_snapshots":[{"event_id":"sha256:2e82face0cb0321d5bc761eb7d011bdecfb544b2814a7521fe2eda9fddc49d4e","target":"graph","created_at":"2026-07-05T09:30:17Z","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/2406.17414/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Robust estimation of the essential matrix, which encodes the relative position and orientation of two cameras, is a fundamental step in structure from motion pipelines. Recent deep-based methods achieved accurate estimation by using complex network architectures that involve graphs, attention layers, and hard pruning steps. Here, we propose a simpler network architecture based on Deep Sets. Given a collection of point matches extracted from two images, our method identifies outlier point matches and models the displacement noise in inlier matches. A weighted DLT module uses these predictions t","authors_text":"Dror Moran, Fadi Khatib, Guy Trostianetsky, Meirav Galun, Ronen Basri, Yuval Margalit","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-06-25T09:37:09Z","title":"Consensus Learning with Deep Sets for Essential Matrix Estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.17414","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":"sha256:128b225c4cdfbc9260b2f637e391d4968fc12b730c3baaec370c922fed4230a4","target":"record","created_at":"2026-07-05T09:30:17Z","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":"52a0a60e68280d24f0651e22339f77321b616e95d2bc539ef840fed07c7a7f27","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-06-25T09:37:09Z","title_canon_sha256":"2383b4da6dc289d40ed4263c01d8a8ed5bcc36bc5d6bcfe3eb84d6dda96dde0e"},"schema_version":"1.0","source":{"id":"2406.17414","kind":"arxiv","version":2}},"canonical_sha256":"3d94873309d1a70f650c9faa67e4d95ccb49df4c8c69b8d682e94582d6897a03","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3d94873309d1a70f650c9faa67e4d95ccb49df4c8c69b8d682e94582d6897a03","first_computed_at":"2026-07-05T09:30:17.789365Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:30:17.789365Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qtCa+slSezgn1rTE1pgWWBJrdidZlmXblXfjGSqIdDW2Y/fuXO7MMzKItRYO/mDAo3xbQslEj7kXnKCRi32KCg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:30:17.789791Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.17414","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:128b225c4cdfbc9260b2f637e391d4968fc12b730c3baaec370c922fed4230a4","sha256:2e82face0cb0321d5bc761eb7d011bdecfb544b2814a7521fe2eda9fddc49d4e"],"state_sha256":"ae2c174511eca44b5ea4a65f29ea425c4a25050c4755d70e633cfec50547137a"}