{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:RFICVLJGS2B7RKSFZNCJCJXST6","short_pith_number":"pith:RFICVLJG","schema_version":"1.0","canonical_sha256":"89502aad269683f8aa45cb449126f29f829490b7e7dcd8cb945f61712f1c32d8","source":{"kind":"arxiv","id":"2308.11441","version":1},"attestation_state":"computed","paper":{"title":"Learning a More Continuous Zero Level Set in Unsigned Distance Fields through Level Set Projection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Baorui Ma, Junsheng Zhou, Shujuan Li, Yu-Shen Liu, Zhizhong Han","submitted_at":"2023-08-22T13:45:35Z","abstract_excerpt":"Latest methods represent shapes with open surfaces using unsigned distance functions (UDFs). They train neural networks to learn UDFs and reconstruct surfaces with the gradients around the zero level set of the UDF. However, the differential networks struggle from learning the zero level set where the UDF is not differentiable, which leads to large errors on unsigned distances and gradients around the zero level set, resulting in highly fragmented and discontinuous surfaces. To resolve this problem, we propose to learn a more continuous zero level set in UDFs with level set projections. Our in"},"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":"2308.11441","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-08-22T13:45:35Z","cross_cats_sorted":[],"title_canon_sha256":"2bb2d3c277cee3e1f8fba717185397487894d66cc5a4430500f2366360b54dac","abstract_canon_sha256":"0f390fd28a4de1d43004575561302a65eb19d4ab025a0d4087eb1c771ccc04ee"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:43:34.725128Z","signature_b64":"bekjmL6VyU5BS/ExXNYm12+GAfzliG8fWVbz5gSpQTMrvnGR/S0y99mSajz1fmX/3ZqId8xc2icJmBH5+z51Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"89502aad269683f8aa45cb449126f29f829490b7e7dcd8cb945f61712f1c32d8","last_reissued_at":"2026-07-05T06:43:34.724722Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:43:34.724722Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Learning a More Continuous Zero Level Set in Unsigned Distance Fields through Level Set Projection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Baorui Ma, Junsheng Zhou, Shujuan Li, Yu-Shen Liu, Zhizhong Han","submitted_at":"2023-08-22T13:45:35Z","abstract_excerpt":"Latest methods represent shapes with open surfaces using unsigned distance functions (UDFs). They train neural networks to learn UDFs and reconstruct surfaces with the gradients around the zero level set of the UDF. However, the differential networks struggle from learning the zero level set where the UDF is not differentiable, which leads to large errors on unsigned distances and gradients around the zero level set, resulting in highly fragmented and discontinuous surfaces. To resolve this problem, we propose to learn a more continuous zero level set in UDFs with level set projections. Our in"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.11441","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/2308.11441/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":"2308.11441","created_at":"2026-07-05T06:43:34.724778+00:00"},{"alias_kind":"arxiv_version","alias_value":"2308.11441v1","created_at":"2026-07-05T06:43:34.724778+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.11441","created_at":"2026-07-05T06:43:34.724778+00:00"},{"alias_kind":"pith_short_12","alias_value":"RFICVLJGS2B7","created_at":"2026-07-05T06:43:34.724778+00:00"},{"alias_kind":"pith_short_16","alias_value":"RFICVLJGS2B7RKSF","created_at":"2026-07-05T06:43:34.724778+00:00"},{"alias_kind":"pith_short_8","alias_value":"RFICVLJG","created_at":"2026-07-05T06:43:34.724778+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/RFICVLJGS2B7RKSFZNCJCJXST6","json":"https://pith.science/pith/RFICVLJGS2B7RKSFZNCJCJXST6.json","graph_json":"https://pith.science/api/pith-number/RFICVLJGS2B7RKSFZNCJCJXST6/graph.json","events_json":"https://pith.science/api/pith-number/RFICVLJGS2B7RKSFZNCJCJXST6/events.json","paper":"https://pith.science/paper/RFICVLJG"},"agent_actions":{"view_html":"https://pith.science/pith/RFICVLJGS2B7RKSFZNCJCJXST6","download_json":"https://pith.science/pith/RFICVLJGS2B7RKSFZNCJCJXST6.json","view_paper":"https://pith.science/paper/RFICVLJG","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2308.11441&json=true","fetch_graph":"https://pith.science/api/pith-number/RFICVLJGS2B7RKSFZNCJCJXST6/graph.json","fetch_events":"https://pith.science/api/pith-number/RFICVLJGS2B7RKSFZNCJCJXST6/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RFICVLJGS2B7RKSFZNCJCJXST6/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RFICVLJGS2B7RKSFZNCJCJXST6/action/storage_attestation","attest_author":"https://pith.science/pith/RFICVLJGS2B7RKSFZNCJCJXST6/action/author_attestation","sign_citation":"https://pith.science/pith/RFICVLJGS2B7RKSFZNCJCJXST6/action/citation_signature","submit_replication":"https://pith.science/pith/RFICVLJGS2B7RKSFZNCJCJXST6/action/replication_record"}},"created_at":"2026-07-05T06:43:34.724778+00:00","updated_at":"2026-07-05T06:43:34.724778+00:00"}