{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:INDSYOZREKPQF2NQKJSX6QVQRP","short_pith_number":"pith:INDSYOZR","schema_version":"1.0","canonical_sha256":"43472c3b31229f02e9b052657f42b08bcf8991d7794e3b33949d2a6cde18c055","source":{"kind":"arxiv","id":"1904.06699","version":2},"attestation_state":"computed","paper":{"title":"Conditional Single-view Shape Generation for Multi-view Stereo Reconstruction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jie Zhou, Jiwen Lu, Shaohui Liu, Wang Zhao, Yi Wei","submitted_at":"2019-04-14T14:16:32Z","abstract_excerpt":"In this paper, we present a new perspective towards image-based shape generation. Most existing deep learning based shape reconstruction methods employ a single-view deterministic model which is sometimes insufficient to determine a single groundtruth shape because the back part is occluded. In this work, we first introduce a conditional generative network to model the uncertainty for single-view reconstruction. Then, we formulate the task of multi-view reconstruction as taking the intersection of the predicted shape spaces on each single image. We design new differentiable guidance including "},"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":"1904.06699","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-14T14:16:32Z","cross_cats_sorted":[],"title_canon_sha256":"36f14161c29f85d335a45a7d43e96a4bcaed4d75c9c9e7518bd69fb17fc807bd","abstract_canon_sha256":"1c8c590a2df305c8a6a82a6d02232fdfb1aeb2d3c87497b23ef6cd5113cf9f58"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:48:04.361901Z","signature_b64":"y2ekpKBqu3I6saE4rIypU6K/5iadnqGQrGufDuADBD2XLaEN5dRYiG04Tmf8JBiOlXL1p7+hlW9o6DOVHjaQBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"43472c3b31229f02e9b052657f42b08bcf8991d7794e3b33949d2a6cde18c055","last_reissued_at":"2026-05-17T23:48:04.361455Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:48:04.361455Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Conditional Single-view Shape Generation for Multi-view Stereo Reconstruction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jie Zhou, Jiwen Lu, Shaohui Liu, Wang Zhao, Yi Wei","submitted_at":"2019-04-14T14:16:32Z","abstract_excerpt":"In this paper, we present a new perspective towards image-based shape generation. Most existing deep learning based shape reconstruction methods employ a single-view deterministic model which is sometimes insufficient to determine a single groundtruth shape because the back part is occluded. In this work, we first introduce a conditional generative network to model the uncertainty for single-view reconstruction. Then, we formulate the task of multi-view reconstruction as taking the intersection of the predicted shape spaces on each single image. We design new differentiable guidance including "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.06699","kind":"arxiv","version":2},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1904.06699","created_at":"2026-05-17T23:48:04.361532+00:00"},{"alias_kind":"arxiv_version","alias_value":"1904.06699v2","created_at":"2026-05-17T23:48:04.361532+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.06699","created_at":"2026-05-17T23:48:04.361532+00:00"},{"alias_kind":"pith_short_12","alias_value":"INDSYOZREKPQ","created_at":"2026-05-18T12:33:18.533446+00:00"},{"alias_kind":"pith_short_16","alias_value":"INDSYOZREKPQF2NQ","created_at":"2026-05-18T12:33:18.533446+00:00"},{"alias_kind":"pith_short_8","alias_value":"INDSYOZR","created_at":"2026-05-18T12:33:18.533446+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/INDSYOZREKPQF2NQKJSX6QVQRP","json":"https://pith.science/pith/INDSYOZREKPQF2NQKJSX6QVQRP.json","graph_json":"https://pith.science/api/pith-number/INDSYOZREKPQF2NQKJSX6QVQRP/graph.json","events_json":"https://pith.science/api/pith-number/INDSYOZREKPQF2NQKJSX6QVQRP/events.json","paper":"https://pith.science/paper/INDSYOZR"},"agent_actions":{"view_html":"https://pith.science/pith/INDSYOZREKPQF2NQKJSX6QVQRP","download_json":"https://pith.science/pith/INDSYOZREKPQF2NQKJSX6QVQRP.json","view_paper":"https://pith.science/paper/INDSYOZR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1904.06699&json=true","fetch_graph":"https://pith.science/api/pith-number/INDSYOZREKPQF2NQKJSX6QVQRP/graph.json","fetch_events":"https://pith.science/api/pith-number/INDSYOZREKPQF2NQKJSX6QVQRP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/INDSYOZREKPQF2NQKJSX6QVQRP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/INDSYOZREKPQF2NQKJSX6QVQRP/action/storage_attestation","attest_author":"https://pith.science/pith/INDSYOZREKPQF2NQKJSX6QVQRP/action/author_attestation","sign_citation":"https://pith.science/pith/INDSYOZREKPQF2NQKJSX6QVQRP/action/citation_signature","submit_replication":"https://pith.science/pith/INDSYOZREKPQF2NQKJSX6QVQRP/action/replication_record"}},"created_at":"2026-05-17T23:48:04.361532+00:00","updated_at":"2026-05-17T23:48:04.361532+00:00"}