{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:TPEU6T6UQZUF2IOPXQQZOGNPNZ","short_pith_number":"pith:TPEU6T6U","canonical_record":{"source":{"id":"2107.05893","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-07-13T07:45:48Z","cross_cats_sorted":[],"title_canon_sha256":"7524d83bb8c7cf3a5920f1b49e98604b9b20c282553156b3ffed9f6ab56f9c3a","abstract_canon_sha256":"6d6ac1086b15f647ea48063fba460da2f6bc556660be6dfea37ee2aedd9988e7"},"schema_version":"1.0"},"canonical_sha256":"9bc94f4fd486685d21cfbc219719af6e637198e5c8f1671073d2a4a7804c0cf2","source":{"kind":"arxiv","id":"2107.05893","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2107.05893","created_at":"2026-07-05T04:30:03Z"},{"alias_kind":"arxiv_version","alias_value":"2107.05893v4","created_at":"2026-07-05T04:30:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2107.05893","created_at":"2026-07-05T04:30:03Z"},{"alias_kind":"pith_short_12","alias_value":"TPEU6T6UQZUF","created_at":"2026-07-05T04:30:03Z"},{"alias_kind":"pith_short_16","alias_value":"TPEU6T6UQZUF2IOP","created_at":"2026-07-05T04:30:03Z"},{"alias_kind":"pith_short_8","alias_value":"TPEU6T6U","created_at":"2026-07-05T04:30:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:TPEU6T6UQZUF2IOPXQQZOGNPNZ","target":"record","payload":{"canonical_record":{"source":{"id":"2107.05893","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-07-13T07:45:48Z","cross_cats_sorted":[],"title_canon_sha256":"7524d83bb8c7cf3a5920f1b49e98604b9b20c282553156b3ffed9f6ab56f9c3a","abstract_canon_sha256":"6d6ac1086b15f647ea48063fba460da2f6bc556660be6dfea37ee2aedd9988e7"},"schema_version":"1.0"},"canonical_sha256":"9bc94f4fd486685d21cfbc219719af6e637198e5c8f1671073d2a4a7804c0cf2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:30:03.695513Z","signature_b64":"/eRFot91lDV0DnXaIGgEw1B/1oaUakWnACCvQNodlvYVSlvIxynSDd+rSDb51AstV5uMPn7ECRrW9yEFo8hDDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9bc94f4fd486685d21cfbc219719af6e637198e5c8f1671073d2a4a7804c0cf2","last_reissued_at":"2026-07-05T04:30:03.695086Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:30:03.695086Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2107.05893","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":"2026-07-05T04:30:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YzK7xNf1c0Eo8jvrF59ABiHQml3/CFzDCS3j7gDeMl4RNIR9+lQ8Co6viQW4DCnebKSeQlXb7GenhJl+8A64Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T00:29:42.014606Z"},"content_sha256":"043a0bb23a0a1e9253b14db5bac685be9cad5d65ebe1e95d5b170985be426414","schema_version":"1.0","event_id":"sha256:043a0bb23a0a1e9253b14db5bac685be9cad5d65ebe1e95d5b170985be426414"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:TPEU6T6UQZUF2IOPXQQZOGNPNZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PU-Flow: a Point Cloud Upsampling Network with Normalizing Flows","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Aihua Mao, Junhui Hou, Yaqi Duan, Ying He, Yong-jin Liu, Zihui Du","submitted_at":"2021-07-13T07:45:48Z","abstract_excerpt":"Point cloud upsampling aims to generate dense point clouds from given sparse ones, which is a challenging task due to the irregular and unordered nature of point sets. To address this issue, we present a novel deep learning-based model, called PU-Flow, which incorporates normalizing flows and weight prediction techniques to produce dense points uniformly distributed on the underlying surface. Specifically, we exploit the invertible characteristics of normalizing flows to transform points between Euclidean and latent spaces and formulate the upsampling process as ensemble of neighbouring points"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2107.05893","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2107.05893/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:30:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"v0OXUnHZy3Bq2xTQps0nFZ8d6cjKUqJy6V2i2MJfKM8Gjxz4J5QevTneXUyESwh2LgE/0URiadOFKvE0pm7qDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T00:29:42.015088Z"},"content_sha256":"de0debe0af58d6c6550d8822111a42e01629c92f769c717646fb394b9373e454","schema_version":"1.0","event_id":"sha256:de0debe0af58d6c6550d8822111a42e01629c92f769c717646fb394b9373e454"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TPEU6T6UQZUF2IOPXQQZOGNPNZ/bundle.json","state_url":"https://pith.science/pith/TPEU6T6UQZUF2IOPXQQZOGNPNZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TPEU6T6UQZUF2IOPXQQZOGNPNZ/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":"2026-08-11T00:29:42Z","links":{"resolver":"https://pith.science/pith/TPEU6T6UQZUF2IOPXQQZOGNPNZ","bundle":"https://pith.science/pith/TPEU6T6UQZUF2IOPXQQZOGNPNZ/bundle.json","state":"https://pith.science/pith/TPEU6T6UQZUF2IOPXQQZOGNPNZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TPEU6T6UQZUF2IOPXQQZOGNPNZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:TPEU6T6UQZUF2IOPXQQZOGNPNZ","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":"6d6ac1086b15f647ea48063fba460da2f6bc556660be6dfea37ee2aedd9988e7","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-07-13T07:45:48Z","title_canon_sha256":"7524d83bb8c7cf3a5920f1b49e98604b9b20c282553156b3ffed9f6ab56f9c3a"},"schema_version":"1.0","source":{"id":"2107.05893","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2107.05893","created_at":"2026-07-05T04:30:03Z"},{"alias_kind":"arxiv_version","alias_value":"2107.05893v4","created_at":"2026-07-05T04:30:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2107.05893","created_at":"2026-07-05T04:30:03Z"},{"alias_kind":"pith_short_12","alias_value":"TPEU6T6UQZUF","created_at":"2026-07-05T04:30:03Z"},{"alias_kind":"pith_short_16","alias_value":"TPEU6T6UQZUF2IOP","created_at":"2026-07-05T04:30:03Z"},{"alias_kind":"pith_short_8","alias_value":"TPEU6T6U","created_at":"2026-07-05T04:30:03Z"}],"graph_snapshots":[{"event_id":"sha256:de0debe0af58d6c6550d8822111a42e01629c92f769c717646fb394b9373e454","target":"graph","created_at":"2026-07-05T04:30:03Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2107.05893/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Point cloud upsampling aims to generate dense point clouds from given sparse ones, which is a challenging task due to the irregular and unordered nature of point sets. To address this issue, we present a novel deep learning-based model, called PU-Flow, which incorporates normalizing flows and weight prediction techniques to produce dense points uniformly distributed on the underlying surface. Specifically, we exploit the invertible characteristics of normalizing flows to transform points between Euclidean and latent spaces and formulate the upsampling process as ensemble of neighbouring points","authors_text":"Aihua Mao, Junhui Hou, Yaqi Duan, Ying He, Yong-jin Liu, Zihui Du","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-07-13T07:45:48Z","title":"PU-Flow: a Point Cloud Upsampling Network with Normalizing Flows"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2107.05893","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":"sha256:043a0bb23a0a1e9253b14db5bac685be9cad5d65ebe1e95d5b170985be426414","target":"record","created_at":"2026-07-05T04:30:03Z","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":"6d6ac1086b15f647ea48063fba460da2f6bc556660be6dfea37ee2aedd9988e7","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-07-13T07:45:48Z","title_canon_sha256":"7524d83bb8c7cf3a5920f1b49e98604b9b20c282553156b3ffed9f6ab56f9c3a"},"schema_version":"1.0","source":{"id":"2107.05893","kind":"arxiv","version":4}},"canonical_sha256":"9bc94f4fd486685d21cfbc219719af6e637198e5c8f1671073d2a4a7804c0cf2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9bc94f4fd486685d21cfbc219719af6e637198e5c8f1671073d2a4a7804c0cf2","first_computed_at":"2026-07-05T04:30:03.695086Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:30:03.695086Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/eRFot91lDV0DnXaIGgEw1B/1oaUakWnACCvQNodlvYVSlvIxynSDd+rSDb51AstV5uMPn7ECRrW9yEFo8hDDA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:30:03.695513Z","signed_message":"canonical_sha256_bytes"},"source_id":"2107.05893","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:043a0bb23a0a1e9253b14db5bac685be9cad5d65ebe1e95d5b170985be426414","sha256:de0debe0af58d6c6550d8822111a42e01629c92f769c717646fb394b9373e454"],"state_sha256":"08fe0a0b899cdedaf0eebc4a13a009b9af2a5b6c1a5441023fa703e9b04bf72b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"668JbGClzk7isPTMWAfR8KWO5KSxHSlLRGCH2phRmfMKUlTZ9bxnXetHgbe+GxrDBVey+TNsIGFqsuGO4XrtAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T00:29:42.019384Z","bundle_sha256":"bc20b170725429536c53550854c287bc1dc9bb401dc0112092ac11990d915b67"}}