{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:TIGRVVBH6LQ3QBM6G5MRQZVTCS","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":"352ddba3665206e25163c747154088ebb0a38014e947e1b5bdcac3653ca5d749","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-23T00:27:23Z","title_canon_sha256":"1f794ec8ccf2bf99293888b221971475f7fbbaac2106cf3bfb53317ba4c050bb"},"schema_version":"1.0","source":{"id":"2505.17358","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.17358","created_at":"2026-07-05T11:08:24Z"},{"alias_kind":"arxiv_version","alias_value":"2505.17358v1","created_at":"2026-07-05T11:08:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.17358","created_at":"2026-07-05T11:08:24Z"},{"alias_kind":"pith_short_12","alias_value":"TIGRVVBH6LQ3","created_at":"2026-07-05T11:08:24Z"},{"alias_kind":"pith_short_16","alias_value":"TIGRVVBH6LQ3QBM6","created_at":"2026-07-05T11:08:24Z"},{"alias_kind":"pith_short_8","alias_value":"TIGRVVBH","created_at":"2026-07-05T11:08:24Z"}],"graph_snapshots":[{"event_id":"sha256:42e4e7094a2ecce77dc2338e5ee87fc460228110b2127e971006c3559eaed68a","target":"graph","created_at":"2026-07-05T11:08:24Z","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/2505.17358/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent monocular metric depth estimation (MMDE) methods have made notable progress towards zero-shot generalization. However, they still exhibit a significant performance drop on out-of-distribution datasets. We address this limitation by injecting defocus blur cues at inference time into Marigold, a \\textit{pre-trained} diffusion model for zero-shot, scale-invariant monocular depth estimation (MDE). Our method effectively turns Marigold into a metric depth predictor in a training-free manner. To incorporate defocus cues, we capture two images with a small and a large aperture from the same vi","authors_text":"Chinmay Talegaonkar, Nicholas Antipa, Nikhil Gandudi Suresh, Priyanka Nagasamudra, Yash Belhe, Zachary Novack","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-23T00:27:23Z","title":"Repurposing Marigold for Zero-Shot Metric Depth Estimation via Defocus Blur Cues"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.17358","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":"sha256:7b374c3f2a5bbc60da5308d059a1103ec77eb8b024e5c9e4aa1ab145fa27977e","target":"record","created_at":"2026-07-05T11:08:24Z","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":"352ddba3665206e25163c747154088ebb0a38014e947e1b5bdcac3653ca5d749","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-23T00:27:23Z","title_canon_sha256":"1f794ec8ccf2bf99293888b221971475f7fbbaac2106cf3bfb53317ba4c050bb"},"schema_version":"1.0","source":{"id":"2505.17358","kind":"arxiv","version":1}},"canonical_sha256":"9a0d1ad427f2e1b8059e37591866b31489954cb8da52dcecc4a26ac1e5a1fdfd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9a0d1ad427f2e1b8059e37591866b31489954cb8da52dcecc4a26ac1e5a1fdfd","first_computed_at":"2026-07-05T11:08:24.626616Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:08:24.626616Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4MLYBSgemTFAl7fTEG3Ezd1wQDEYhQTocIDHMPExnp6m0WK62ixhbcbP/ndi7t5pk2iMM4yl8WgJRcb2DDOyBw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:08:24.627095Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.17358","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7b374c3f2a5bbc60da5308d059a1103ec77eb8b024e5c9e4aa1ab145fa27977e","sha256:42e4e7094a2ecce77dc2338e5ee87fc460228110b2127e971006c3559eaed68a"],"state_sha256":"0125cd455a1c4886fccb525b51d33298507fdd4572069b2c5acf4ad5944edecd"}