{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:G3RV354EFLRZNUAYNU2JLIY25X","short_pith_number":"pith:G3RV354E","canonical_record":{"source":{"id":"1407.3840","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-07-14T22:52:05Z","cross_cats_sorted":[],"title_canon_sha256":"8044d4447a0786aa969be2a316c67bcb9fbd92f64dd7bb3356f3c2ed6bc662e4","abstract_canon_sha256":"1b031515be0f121235ed83ba431bfa0f56c56e54df23983380d6c6878fe1483a"},"schema_version":"1.0"},"canonical_sha256":"36e35df7842ae396d0186d3495a31aede4bf80f147868f3a62194c1af8e79001","source":{"kind":"arxiv","id":"1407.3840","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1407.3840","created_at":"2026-05-18T02:27:18Z"},{"alias_kind":"arxiv_version","alias_value":"1407.3840v4","created_at":"2026-05-18T02:27:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1407.3840","created_at":"2026-05-18T02:27:18Z"},{"alias_kind":"pith_short_12","alias_value":"G3RV354EFLRZ","created_at":"2026-05-18T12:28:28Z"},{"alias_kind":"pith_short_16","alias_value":"G3RV354EFLRZNUAY","created_at":"2026-05-18T12:28:28Z"},{"alias_kind":"pith_short_8","alias_value":"G3RV354E","created_at":"2026-05-18T12:28:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:G3RV354EFLRZNUAYNU2JLIY25X","target":"record","payload":{"canonical_record":{"source":{"id":"1407.3840","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-07-14T22:52:05Z","cross_cats_sorted":[],"title_canon_sha256":"8044d4447a0786aa969be2a316c67bcb9fbd92f64dd7bb3356f3c2ed6bc662e4","abstract_canon_sha256":"1b031515be0f121235ed83ba431bfa0f56c56e54df23983380d6c6878fe1483a"},"schema_version":"1.0"},"canonical_sha256":"36e35df7842ae396d0186d3495a31aede4bf80f147868f3a62194c1af8e79001","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:27:18.576810Z","signature_b64":"u8U0RDK8BmRfuCD72bcay9mfqF+BgqB2MNL/LWB0xdnrMiUtlkC+KKbn/ufIIqff1C/v9JQc62LjUpg8Frt6Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"36e35df7842ae396d0186d3495a31aede4bf80f147868f3a62194c1af8e79001","last_reissued_at":"2026-05-18T02:27:18.576017Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:27:18.576017Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1407.3840","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T02:27:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VElGLCA9M8uouBZvqhTTYC1qRjMxZGutBTQFIwUaQZSwM95/zax+jOt+noElg53aVEwFoJZviHllTgtXmr0eCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T20:53:30.132860Z"},"content_sha256":"b3437f271291346c2e6d432d9f7ea05c20c96bb66d9eb1002abf216c573bd9b2","schema_version":"1.0","event_id":"sha256:b3437f271291346c2e6d432d9f7ea05c20c96bb66d9eb1002abf216c573bd9b2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:G3RV354EFLRZNUAYNU2JLIY25X","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Depth Reconstruction from Sparse Samples: Representation, Algorithm, and Sampling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Lee-Kang Liu, Stanley H. Chan, Truong Q. Nguyen","submitted_at":"2014-07-14T22:52:05Z","abstract_excerpt":"The rapid development of 3D technology and computer vision applications have motivated a thrust of methodologies for depth acquisition and estimation. However, most existing hardware and software methods have limited performance due to poor depth precision, low resolution and high computational cost. In this paper, we present a computationally efficient method to recover dense depth maps from sparse measurements. We make three contributions. First, we provide empirical evidence that depth maps can be encoded much more sparsely than natural images by using common dictionaries such as wavelets a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1407.3840","kind":"arxiv","version":4},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T02:27:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MxLcARavfMIqL35qp22qFrLy/UR4M2YPRn9yW3pyTeDVe1dIIlhaHJE6bee/NHZuUDa/GJ5LLlmgigk6Q6VfBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T20:53:30.133195Z"},"content_sha256":"f8d92e79c27d5343a2d51ef91174bb649683efb5c5bfeec5a1b6cf9f1f18d4b7","schema_version":"1.0","event_id":"sha256:f8d92e79c27d5343a2d51ef91174bb649683efb5c5bfeec5a1b6cf9f1f18d4b7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/G3RV354EFLRZNUAYNU2JLIY25X/bundle.json","state_url":"https://pith.science/pith/G3RV354EFLRZNUAYNU2JLIY25X/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/G3RV354EFLRZNUAYNU2JLIY25X/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-10T20:53:30Z","links":{"resolver":"https://pith.science/pith/G3RV354EFLRZNUAYNU2JLIY25X","bundle":"https://pith.science/pith/G3RV354EFLRZNUAYNU2JLIY25X/bundle.json","state":"https://pith.science/pith/G3RV354EFLRZNUAYNU2JLIY25X/state.json","well_known_bundle":"https://pith.science/.well-known/pith/G3RV354EFLRZNUAYNU2JLIY25X/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:G3RV354EFLRZNUAYNU2JLIY25X","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":"1b031515be0f121235ed83ba431bfa0f56c56e54df23983380d6c6878fe1483a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-07-14T22:52:05Z","title_canon_sha256":"8044d4447a0786aa969be2a316c67bcb9fbd92f64dd7bb3356f3c2ed6bc662e4"},"schema_version":"1.0","source":{"id":"1407.3840","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1407.3840","created_at":"2026-05-18T02:27:18Z"},{"alias_kind":"arxiv_version","alias_value":"1407.3840v4","created_at":"2026-05-18T02:27:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1407.3840","created_at":"2026-05-18T02:27:18Z"},{"alias_kind":"pith_short_12","alias_value":"G3RV354EFLRZ","created_at":"2026-05-18T12:28:28Z"},{"alias_kind":"pith_short_16","alias_value":"G3RV354EFLRZNUAY","created_at":"2026-05-18T12:28:28Z"},{"alias_kind":"pith_short_8","alias_value":"G3RV354E","created_at":"2026-05-18T12:28:28Z"}],"graph_snapshots":[{"event_id":"sha256:f8d92e79c27d5343a2d51ef91174bb649683efb5c5bfeec5a1b6cf9f1f18d4b7","target":"graph","created_at":"2026-05-18T02:27:18Z","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"},"paper":{"abstract_excerpt":"The rapid development of 3D technology and computer vision applications have motivated a thrust of methodologies for depth acquisition and estimation. However, most existing hardware and software methods have limited performance due to poor depth precision, low resolution and high computational cost. In this paper, we present a computationally efficient method to recover dense depth maps from sparse measurements. We make three contributions. First, we provide empirical evidence that depth maps can be encoded much more sparsely than natural images by using common dictionaries such as wavelets a","authors_text":"Lee-Kang Liu, Stanley H. Chan, Truong Q. Nguyen","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-07-14T22:52:05Z","title":"Depth Reconstruction from Sparse Samples: Representation, Algorithm, and Sampling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1407.3840","kind":"arxiv","version":4},"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:b3437f271291346c2e6d432d9f7ea05c20c96bb66d9eb1002abf216c573bd9b2","target":"record","created_at":"2026-05-18T02:27:18Z","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":"1b031515be0f121235ed83ba431bfa0f56c56e54df23983380d6c6878fe1483a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-07-14T22:52:05Z","title_canon_sha256":"8044d4447a0786aa969be2a316c67bcb9fbd92f64dd7bb3356f3c2ed6bc662e4"},"schema_version":"1.0","source":{"id":"1407.3840","kind":"arxiv","version":4}},"canonical_sha256":"36e35df7842ae396d0186d3495a31aede4bf80f147868f3a62194c1af8e79001","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"36e35df7842ae396d0186d3495a31aede4bf80f147868f3a62194c1af8e79001","first_computed_at":"2026-05-18T02:27:18.576017Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:27:18.576017Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"u8U0RDK8BmRfuCD72bcay9mfqF+BgqB2MNL/LWB0xdnrMiUtlkC+KKbn/ufIIqff1C/v9JQc62LjUpg8Frt6Cg==","signature_status":"signed_v1","signed_at":"2026-05-18T02:27:18.576810Z","signed_message":"canonical_sha256_bytes"},"source_id":"1407.3840","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b3437f271291346c2e6d432d9f7ea05c20c96bb66d9eb1002abf216c573bd9b2","sha256:f8d92e79c27d5343a2d51ef91174bb649683efb5c5bfeec5a1b6cf9f1f18d4b7"],"state_sha256":"8f962546f4afef61951a20285aed2c625599ccb09faad10fd64884dae450f61c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YUbNlHJwu6aai7woFzZERJQWdXkM19qEdLlrijR8j7wMn3CWN+szjoWD5Zy1Y2vZwq2BCL7cwpaP3mxRqvhuCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-10T20:53:30.135206Z","bundle_sha256":"23e2179a0e616d97d5909340b3620d83117294dc2c3474e352e4d3a97af65850"}}