{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:ND3ZBGGBGYPYOYXDFSGZJFV2CL","short_pith_number":"pith:ND3ZBGGB","schema_version":"1.0","canonical_sha256":"68f79098c1361f8762e32c8d9496ba12e309fc0093df1d08a3476c4301302c40","source":{"kind":"arxiv","id":"2304.06334","version":1},"attestation_state":"computed","paper":{"title":"iDisc: Internal Discretization for Monocular Depth Estimation","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Christos Sakaridis, Fisher Yu, Luigi Piccinelli","submitted_at":"2023-04-13T08:29:59Z","abstract_excerpt":"Monocular depth estimation is fundamental for 3D scene understanding and downstream applications. However, even under the supervised setup, it is still challenging and ill-posed due to the lack of full geometric constraints. Although a scene can consist of millions of pixels, there are fewer high-level patterns. We propose iDisc to learn those patterns with internal discretized representations. The method implicitly partitions the scene into a set of high-level patterns. In particular, our new module, Internal Discretization (ID), implements a continuous-discrete-continuous bottleneck to learn"},"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":"2304.06334","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-04-13T08:29:59Z","cross_cats_sorted":[],"title_canon_sha256":"29407c014f4fc9206cff3af9955b8fd7a9e1cf1cae559980740700bcbf1ddaf4","abstract_canon_sha256":"9253207ade6891397fc2bfa34fde3de19387fb03b7cb93a91f262d085eb6ff3a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:00:42.209977Z","signature_b64":"ecsj+o2LaIrS64ApTB8pCL0CXvZD9nHAm4ki7eUYZqAtaG2aPaYQzELaSM7JjOrxBJIUgupsrzD5AiWByU86Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"68f79098c1361f8762e32c8d9496ba12e309fc0093df1d08a3476c4301302c40","last_reissued_at":"2026-07-05T06:00:42.209527Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:00:42.209527Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"iDisc: Internal Discretization for Monocular Depth Estimation","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Christos Sakaridis, Fisher Yu, Luigi Piccinelli","submitted_at":"2023-04-13T08:29:59Z","abstract_excerpt":"Monocular depth estimation is fundamental for 3D scene understanding and downstream applications. However, even under the supervised setup, it is still challenging and ill-posed due to the lack of full geometric constraints. Although a scene can consist of millions of pixels, there are fewer high-level patterns. We propose iDisc to learn those patterns with internal discretized representations. The method implicitly partitions the scene into a set of high-level patterns. In particular, our new module, Internal Discretization (ID), implements a continuous-discrete-continuous bottleneck to learn"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.06334","kind":"arxiv","version":1},"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/2304.06334/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":"2304.06334","created_at":"2026-07-05T06:00:42.209584+00:00"},{"alias_kind":"arxiv_version","alias_value":"2304.06334v1","created_at":"2026-07-05T06:00:42.209584+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.06334","created_at":"2026-07-05T06:00:42.209584+00:00"},{"alias_kind":"pith_short_12","alias_value":"ND3ZBGGBGYPY","created_at":"2026-07-05T06:00:42.209584+00:00"},{"alias_kind":"pith_short_16","alias_value":"ND3ZBGGBGYPYOYXD","created_at":"2026-07-05T06:00:42.209584+00:00"},{"alias_kind":"pith_short_8","alias_value":"ND3ZBGGB","created_at":"2026-07-05T06:00:42.209584+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ND3ZBGGBGYPYOYXDFSGZJFV2CL","json":"https://pith.science/pith/ND3ZBGGBGYPYOYXDFSGZJFV2CL.json","graph_json":"https://pith.science/api/pith-number/ND3ZBGGBGYPYOYXDFSGZJFV2CL/graph.json","events_json":"https://pith.science/api/pith-number/ND3ZBGGBGYPYOYXDFSGZJFV2CL/events.json","paper":"https://pith.science/paper/ND3ZBGGB"},"agent_actions":{"view_html":"https://pith.science/pith/ND3ZBGGBGYPYOYXDFSGZJFV2CL","download_json":"https://pith.science/pith/ND3ZBGGBGYPYOYXDFSGZJFV2CL.json","view_paper":"https://pith.science/paper/ND3ZBGGB","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2304.06334&json=true","fetch_graph":"https://pith.science/api/pith-number/ND3ZBGGBGYPYOYXDFSGZJFV2CL/graph.json","fetch_events":"https://pith.science/api/pith-number/ND3ZBGGBGYPYOYXDFSGZJFV2CL/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ND3ZBGGBGYPYOYXDFSGZJFV2CL/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ND3ZBGGBGYPYOYXDFSGZJFV2CL/action/storage_attestation","attest_author":"https://pith.science/pith/ND3ZBGGBGYPYOYXDFSGZJFV2CL/action/author_attestation","sign_citation":"https://pith.science/pith/ND3ZBGGBGYPYOYXDFSGZJFV2CL/action/citation_signature","submit_replication":"https://pith.science/pith/ND3ZBGGBGYPYOYXDFSGZJFV2CL/action/replication_record"}},"created_at":"2026-07-05T06:00:42.209584+00:00","updated_at":"2026-07-05T06:00:42.209584+00:00"}