{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:U7DDL7L3CCVRFZO3GKOJPO5N2V","short_pith_number":"pith:U7DDL7L3","schema_version":"1.0","canonical_sha256":"a7c635fd7b10ab12e5db329c97bbadd56c888cfdd66fdd35364cf2c8a61b633c","source":{"kind":"arxiv","id":"2210.10414","version":3},"attestation_state":"computed","paper":{"title":"High-Resolution Depth Estimation for 360-degree Panoramas through Perspective and Panoramic Depth Images Registration","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chi-Han Peng, Jiayao Zhang","submitted_at":"2022-10-19T09:25:12Z","abstract_excerpt":"We propose a novel approach to compute high-resolution (2048x1024 and higher) depths for panoramas that is significantly faster and qualitatively and qualitatively more accurate than the current state-of-the-art method (360MonoDepth). As traditional neural network-based methods have limitations in the output image sizes (up to 1024x512) due to GPU memory constraints, both 360MonoDepth and our method rely on stitching multiple perspective disparity or depth images to come out a unified panoramic depth map. However, to achieve globally consistent stitching, 360MonoDepth relied on solving extensi"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2210.10414","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-10-19T09:25:12Z","cross_cats_sorted":[],"title_canon_sha256":"8678bfa1df17306e1508fdf3ce8ab11381983b082393b4bd020e725e6d8a2600","abstract_canon_sha256":"570341726ca640b4aa3604d4d5b116f8bae73fcdfb5592cddb9873d60a81a0c5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:10:41.115074Z","signature_b64":"MQX/iNZsJG05OddVJHzoJJAQi3v+F4t7lS4k6chZvwqVzVvNdJebBdlcN6vrtRgernWFVXuhsOG7+NrjdFE2Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a7c635fd7b10ab12e5db329c97bbadd56c888cfdd66fdd35364cf2c8a61b633c","last_reissued_at":"2026-07-05T05:10:41.114533Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:10:41.114533Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"High-Resolution Depth Estimation for 360-degree Panoramas through Perspective and Panoramic Depth Images Registration","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chi-Han Peng, Jiayao Zhang","submitted_at":"2022-10-19T09:25:12Z","abstract_excerpt":"We propose a novel approach to compute high-resolution (2048x1024 and higher) depths for panoramas that is significantly faster and qualitatively and qualitatively more accurate than the current state-of-the-art method (360MonoDepth). As traditional neural network-based methods have limitations in the output image sizes (up to 1024x512) due to GPU memory constraints, both 360MonoDepth and our method rely on stitching multiple perspective disparity or depth images to come out a unified panoramic depth map. However, to achieve globally consistent stitching, 360MonoDepth relied on solving extensi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.10414","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2210.10414/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2210.10414","created_at":"2026-07-05T05:10:41.114591+00:00"},{"alias_kind":"arxiv_version","alias_value":"2210.10414v3","created_at":"2026-07-05T05:10:41.114591+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.10414","created_at":"2026-07-05T05:10:41.114591+00:00"},{"alias_kind":"pith_short_12","alias_value":"U7DDL7L3CCVR","created_at":"2026-07-05T05:10:41.114591+00:00"},{"alias_kind":"pith_short_16","alias_value":"U7DDL7L3CCVRFZO3","created_at":"2026-07-05T05:10:41.114591+00:00"},{"alias_kind":"pith_short_8","alias_value":"U7DDL7L3","created_at":"2026-07-05T05:10:41.114591+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.31086","citing_title":"CasaMaestro: Multi-View Panoramas for House-Scale 3D Reconstruction","ref_index":21,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/U7DDL7L3CCVRFZO3GKOJPO5N2V","json":"https://pith.science/pith/U7DDL7L3CCVRFZO3GKOJPO5N2V.json","graph_json":"https://pith.science/api/pith-number/U7DDL7L3CCVRFZO3GKOJPO5N2V/graph.json","events_json":"https://pith.science/api/pith-number/U7DDL7L3CCVRFZO3GKOJPO5N2V/events.json","paper":"https://pith.science/paper/U7DDL7L3"},"agent_actions":{"view_html":"https://pith.science/pith/U7DDL7L3CCVRFZO3GKOJPO5N2V","download_json":"https://pith.science/pith/U7DDL7L3CCVRFZO3GKOJPO5N2V.json","view_paper":"https://pith.science/paper/U7DDL7L3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2210.10414&json=true","fetch_graph":"https://pith.science/api/pith-number/U7DDL7L3CCVRFZO3GKOJPO5N2V/graph.json","fetch_events":"https://pith.science/api/pith-number/U7DDL7L3CCVRFZO3GKOJPO5N2V/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/U7DDL7L3CCVRFZO3GKOJPO5N2V/action/timestamp_anchor","attest_storage":"https://pith.science/pith/U7DDL7L3CCVRFZO3GKOJPO5N2V/action/storage_attestation","attest_author":"https://pith.science/pith/U7DDL7L3CCVRFZO3GKOJPO5N2V/action/author_attestation","sign_citation":"https://pith.science/pith/U7DDL7L3CCVRFZO3GKOJPO5N2V/action/citation_signature","submit_replication":"https://pith.science/pith/U7DDL7L3CCVRFZO3GKOJPO5N2V/action/replication_record"}},"created_at":"2026-07-05T05:10:41.114591+00:00","updated_at":"2026-07-05T05:10:41.114591+00:00"}