{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:WY23RAGD33ARZZQN2LNET7NFLX","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":"88eb59f67d85924186d50cdf08e8ef2e9cf183c7cf64da96c4cf4d1effb27106","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-29T17:12:03Z","title_canon_sha256":"77b8f4535afc1b78d115accc9be6a31fcba1260da0607c33be9fbabd199e77d9"},"schema_version":"1.0","source":{"id":"2607.27139","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.27139","created_at":"2026-07-30T01:23:51Z"},{"alias_kind":"arxiv_version","alias_value":"2607.27139v1","created_at":"2026-07-30T01:23:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.27139","created_at":"2026-07-30T01:23:51Z"},{"alias_kind":"pith_short_12","alias_value":"WY23RAGD33AR","created_at":"2026-07-30T01:23:51Z"},{"alias_kind":"pith_short_16","alias_value":"WY23RAGD33ARZZQN","created_at":"2026-07-30T01:23:51Z"},{"alias_kind":"pith_short_8","alias_value":"WY23RAGD","created_at":"2026-07-30T01:23:51Z"}],"graph_snapshots":[{"event_id":"sha256:765116bc268234a4a6e7bc449dd35ceee547202dd884c40b992509a341186c6d","target":"graph","created_at":"2026-07-30T01:23:51Z","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/2607.27139/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Accurate 3D reconstruction from satellite imagery typically relies on near-simultaneous stereo pairs, limiting its applicability to diachronic settings where multi-date images exhibit varying seasonal and illumination conditions. Training dense stereo matching models robust to appearance changes is a long-standing challenge, as aligned multi-date imagery and ground-truth geometry are costly to obtain at scale. We propose SeasonStereo, a scalable framework that addresses disparity estimation from diachronic satellite images by training on synthetic image pairs with controlled seasonal appearanc","authors_text":"\\'Alvaro D\\'iaz-Laureano, El\\'ias Masquil, Gabriele Facciolo, Pablo Arias, Roger Mar\\'i","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-29T17:12:03Z","title":"SeasonStereo: Robust Dense Stereo Matching for Multi-Date Satellite Imagery via Generative AI"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.27139","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":"sha256:336681d4bfeb750d3d36a8702d634ca8d62bf065c34eee18b98447c3309526d9","target":"record","created_at":"2026-07-30T01:23:51Z","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":"88eb59f67d85924186d50cdf08e8ef2e9cf183c7cf64da96c4cf4d1effb27106","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-29T17:12:03Z","title_canon_sha256":"77b8f4535afc1b78d115accc9be6a31fcba1260da0607c33be9fbabd199e77d9"},"schema_version":"1.0","source":{"id":"2607.27139","kind":"arxiv","version":1}},"canonical_sha256":"b635b880c3dec11ce60dd2da49fda55ddc25d0d1b117d740dce9073fef657094","receipt":{"builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b635b880c3dec11ce60dd2da49fda55ddc25d0d1b117d740dce9073fef657094","first_computed_at":"2026-07-30T01:23:51.306235Z","kind":"pith_receipt","last_reissued_at":"2026-07-30T01:23:51.306235Z","receipt_version":"0.3","signature_status":"unsigned_v0"},"source_id":"2607.27139","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:336681d4bfeb750d3d36a8702d634ca8d62bf065c34eee18b98447c3309526d9","sha256:765116bc268234a4a6e7bc449dd35ceee547202dd884c40b992509a341186c6d"],"state_sha256":"d4cfe53c0b6ca2d2713995e3c822a65eb711dd7a855933760feb043f7d52d21d"}