{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:UU7GNW6JIMEBMZA3Y5PFA3WPKE","short_pith_number":"pith:UU7GNW6J","canonical_record":{"source":{"id":"2210.04072","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-10-08T17:58:20Z","cross_cats_sorted":[],"title_canon_sha256":"decef0d682914ad38b26d1fcde299a0c78cccf3c9f43db793789c11cfc8f8c65","abstract_canon_sha256":"706b21596df963ac1744109b1492ade1a7b2c5856ac73fb1314a83183d8d9b8e"},"schema_version":"1.0"},"canonical_sha256":"a53e66dbc9430816641bc75e506ecf510471b96a4c327e3b3ab9bc25afe35c80","source":{"kind":"arxiv","id":"2210.04072","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.04072","created_at":"2026-07-05T05:04:35Z"},{"alias_kind":"arxiv_version","alias_value":"2210.04072v1","created_at":"2026-07-05T05:04:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.04072","created_at":"2026-07-05T05:04:35Z"},{"alias_kind":"pith_short_12","alias_value":"UU7GNW6JIMEB","created_at":"2026-07-05T05:04:35Z"},{"alias_kind":"pith_short_16","alias_value":"UU7GNW6JIMEBMZA3","created_at":"2026-07-05T05:04:35Z"},{"alias_kind":"pith_short_8","alias_value":"UU7GNW6J","created_at":"2026-07-05T05:04:35Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:UU7GNW6JIMEBMZA3Y5PFA3WPKE","target":"record","payload":{"canonical_record":{"source":{"id":"2210.04072","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-10-08T17:58:20Z","cross_cats_sorted":[],"title_canon_sha256":"decef0d682914ad38b26d1fcde299a0c78cccf3c9f43db793789c11cfc8f8c65","abstract_canon_sha256":"706b21596df963ac1744109b1492ade1a7b2c5856ac73fb1314a83183d8d9b8e"},"schema_version":"1.0"},"canonical_sha256":"a53e66dbc9430816641bc75e506ecf510471b96a4c327e3b3ab9bc25afe35c80","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:04:35.522871Z","signature_b64":"+BPZEqnow+sibARfNkKYvMLdnAFfDszmZq/3SrVMNOjqMph+UG0/kDbdWcSt6Sz0loQG1HQ3VDmHBJDdaxZYBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a53e66dbc9430816641bc75e506ecf510471b96a4c327e3b3ab9bc25afe35c80","last_reissued_at":"2026-07-05T05:04:35.522532Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:04:35.522532Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2210.04072","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:04:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"t9q4Hbcg3Ju0PA2na14mhztAqU2LWSXaVD+VN6jLNUa87KB+dMsli+/35o5Mh3QE/GXFrYTtEyiOZV3gUWXVBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T19:24:59.187182Z"},"content_sha256":"f1516100213f15548fe34924b3619411bea61b5134bb6f09ba1e9c86e9e09b6c","schema_version":"1.0","event_id":"sha256:f1516100213f15548fe34924b3619411bea61b5134bb6f09ba1e9c86e9e09b6c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:UU7GNW6JIMEBMZA3Y5PFA3WPKE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Flow-based GAN for 3D Point Cloud Generation from a Single Image","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"George Vosselman, Michael Ying Yang, Yao Wei","submitted_at":"2022-10-08T17:58:20Z","abstract_excerpt":"Generating a 3D point cloud from a single 2D image is of great importance for 3D scene understanding applications. To reconstruct the whole 3D shape of the object shown in the image, the existing deep learning based approaches use either explicit or implicit generative modeling of point clouds, which, however, suffer from limited quality. In this work, we aim to alleviate this issue by introducing a hybrid explicit-implicit generative modeling scheme, which inherits the flow-based explicit generative models for sampling point clouds with arbitrary resolutions while improving the detailed 3D st"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.04072","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/2210.04072/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":"2026-07-05T05:04:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NpnNIUCg93WvRG9uKQowm7Lx0Zucc1hVIrqjYnexzEYZqXQJe1N2J0ndr1r3LO1evizbrMIEibu6lhSJWrGmAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T19:24:59.188188Z"},"content_sha256":"5ec5262fd13aca0a6068827cc34c9fb9a54da4a64cf5fc555e08364a1caf76d0","schema_version":"1.0","event_id":"sha256:5ec5262fd13aca0a6068827cc34c9fb9a54da4a64cf5fc555e08364a1caf76d0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UU7GNW6JIMEBMZA3Y5PFA3WPKE/bundle.json","state_url":"https://pith.science/pith/UU7GNW6JIMEBMZA3Y5PFA3WPKE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UU7GNW6JIMEBMZA3Y5PFA3WPKE/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":"2026-08-05T19:24:59Z","links":{"resolver":"https://pith.science/pith/UU7GNW6JIMEBMZA3Y5PFA3WPKE","bundle":"https://pith.science/pith/UU7GNW6JIMEBMZA3Y5PFA3WPKE/bundle.json","state":"https://pith.science/pith/UU7GNW6JIMEBMZA3Y5PFA3WPKE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UU7GNW6JIMEBMZA3Y5PFA3WPKE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:UU7GNW6JIMEBMZA3Y5PFA3WPKE","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":"706b21596df963ac1744109b1492ade1a7b2c5856ac73fb1314a83183d8d9b8e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-10-08T17:58:20Z","title_canon_sha256":"decef0d682914ad38b26d1fcde299a0c78cccf3c9f43db793789c11cfc8f8c65"},"schema_version":"1.0","source":{"id":"2210.04072","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.04072","created_at":"2026-07-05T05:04:35Z"},{"alias_kind":"arxiv_version","alias_value":"2210.04072v1","created_at":"2026-07-05T05:04:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.04072","created_at":"2026-07-05T05:04:35Z"},{"alias_kind":"pith_short_12","alias_value":"UU7GNW6JIMEB","created_at":"2026-07-05T05:04:35Z"},{"alias_kind":"pith_short_16","alias_value":"UU7GNW6JIMEBMZA3","created_at":"2026-07-05T05:04:35Z"},{"alias_kind":"pith_short_8","alias_value":"UU7GNW6J","created_at":"2026-07-05T05:04:35Z"}],"graph_snapshots":[{"event_id":"sha256:5ec5262fd13aca0a6068827cc34c9fb9a54da4a64cf5fc555e08364a1caf76d0","target":"graph","created_at":"2026-07-05T05:04:35Z","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/2210.04072/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Generating a 3D point cloud from a single 2D image is of great importance for 3D scene understanding applications. To reconstruct the whole 3D shape of the object shown in the image, the existing deep learning based approaches use either explicit or implicit generative modeling of point clouds, which, however, suffer from limited quality. In this work, we aim to alleviate this issue by introducing a hybrid explicit-implicit generative modeling scheme, which inherits the flow-based explicit generative models for sampling point clouds with arbitrary resolutions while improving the detailed 3D st","authors_text":"George Vosselman, Michael Ying Yang, Yao Wei","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-10-08T17:58:20Z","title":"Flow-based GAN for 3D Point Cloud Generation from a Single Image"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.04072","kind":"arxiv","version":1},"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:f1516100213f15548fe34924b3619411bea61b5134bb6f09ba1e9c86e9e09b6c","target":"record","created_at":"2026-07-05T05:04:35Z","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":"706b21596df963ac1744109b1492ade1a7b2c5856ac73fb1314a83183d8d9b8e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-10-08T17:58:20Z","title_canon_sha256":"decef0d682914ad38b26d1fcde299a0c78cccf3c9f43db793789c11cfc8f8c65"},"schema_version":"1.0","source":{"id":"2210.04072","kind":"arxiv","version":1}},"canonical_sha256":"a53e66dbc9430816641bc75e506ecf510471b96a4c327e3b3ab9bc25afe35c80","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a53e66dbc9430816641bc75e506ecf510471b96a4c327e3b3ab9bc25afe35c80","first_computed_at":"2026-07-05T05:04:35.522532Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:04:35.522532Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+BPZEqnow+sibARfNkKYvMLdnAFfDszmZq/3SrVMNOjqMph+UG0/kDbdWcSt6Sz0loQG1HQ3VDmHBJDdaxZYBA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:04:35.522871Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.04072","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f1516100213f15548fe34924b3619411bea61b5134bb6f09ba1e9c86e9e09b6c","sha256:5ec5262fd13aca0a6068827cc34c9fb9a54da4a64cf5fc555e08364a1caf76d0"],"state_sha256":"0261a4466763814ecf98c852f31824c119d56a6b5c633dc611d143c1878ff4e4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"I4lJ1ISlIDKU5ShpPslRSvzd4bfsqdG4h2CcR8YrxC+vTaHLOTpmnmX9HA0sKDjuVyitHrjVdlT2C84X/XTWAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T19:24:59.195676Z","bundle_sha256":"274ec0a0534288f8f953ddce60a0bf37c0d7e66e6d8d34fbd020344449cb0a75"}}