{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:GBUNSHA6Z624FFVSX5UXE3GPH3","short_pith_number":"pith:GBUNSHA6","canonical_record":{"source":{"id":"2202.08526","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-02-17T09:05:10Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"ee2a12f58be48ffdf22bf4e87bd18db8690821b4205f0eaa541d421f5c96391a","abstract_canon_sha256":"801d6042fe0c291a078451fb64a3b6ad3d9af077f430765840675bba12cf9f60"},"schema_version":"1.0"},"canonical_sha256":"3068d91c1ecfb5c296b2bf69726ccf3eecf7c7c12c76a9fdbbbfa3f0faf2b293","source":{"kind":"arxiv","id":"2202.08526","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2202.08526","created_at":"2026-07-05T04:55:50Z"},{"alias_kind":"arxiv_version","alias_value":"2202.08526v1","created_at":"2026-07-05T04:55:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.08526","created_at":"2026-07-05T04:55:50Z"},{"alias_kind":"pith_short_12","alias_value":"GBUNSHA6Z624","created_at":"2026-07-05T04:55:50Z"},{"alias_kind":"pith_short_16","alias_value":"GBUNSHA6Z624FFVS","created_at":"2026-07-05T04:55:50Z"},{"alias_kind":"pith_short_8","alias_value":"GBUNSHA6","created_at":"2026-07-05T04:55:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:GBUNSHA6Z624FFVSX5UXE3GPH3","target":"record","payload":{"canonical_record":{"source":{"id":"2202.08526","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-02-17T09:05:10Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"ee2a12f58be48ffdf22bf4e87bd18db8690821b4205f0eaa541d421f5c96391a","abstract_canon_sha256":"801d6042fe0c291a078451fb64a3b6ad3d9af077f430765840675bba12cf9f60"},"schema_version":"1.0"},"canonical_sha256":"3068d91c1ecfb5c296b2bf69726ccf3eecf7c7c12c76a9fdbbbfa3f0faf2b293","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:55:50.960577Z","signature_b64":"kUljgaxmBMJyqPBuT4WX7zHgWugR0upP9Xin77ASc3fiXQRvPlO8QcSLhryF+FimgxFma96Yq0O7W4qrosZeBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3068d91c1ecfb5c296b2bf69726ccf3eecf7c7c12c76a9fdbbbfa3f0faf2b293","last_reissued_at":"2026-07-05T04:55:50.959664Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:55:50.959664Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2202.08526","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":"2026-07-05T04:55:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iGlIXwDlIuKvInPjCVv4UeT5BZAt8v/W7Do8GscZ+HtWYlcCA/h/A9ogGUyL7Dx7UFi0qz6eu9wsdLCI6jnwAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T07:38:33.933682Z"},"content_sha256":"5fa97058d237b6e30207b3fce2b41dc72d81d688df1d2ec12dcc3be701bced38","schema_version":"1.0","event_id":"sha256:5fa97058d237b6e30207b3fce2b41dc72d81d688df1d2ec12dcc3be701bced38"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:GBUNSHA6Z624FFVSX5UXE3GPH3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Point Cloud Generation with Continuous Conditioning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CV","authors_text":"Andre B\\\"uhler, David Peter, Fabian B. Flohr, J. Marius Z\\\"ollner, Larissa T. Triess","submitted_at":"2022-02-17T09:05:10Z","abstract_excerpt":"Generative models can be used to synthesize 3D objects of high quality and diversity. However, there is typically no control over the properties of the generated object.This paper proposes a novel generative adversarial network (GAN) setup that generates 3D point cloud shapes conditioned on a continuous parameter. In an exemplary application, we use this to guide the generative process to create a 3D object with a custom-fit shape. We formulate this generation process in a multi-task setting by using the concept of auxiliary classifier GANs. Further, we propose to sample the generator label in"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.08526","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/2202.08526/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":"2026-07-05T04:55:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"l/bohllsewFpVhehkjTDKL4GRWF+Hwd+Com64KcDQWmOQ5zjleI3aVzvHk36jpa7GLPFtlwXQcFoGq2I+0xQCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T07:38:33.934614Z"},"content_sha256":"fbcf2439dac459b530991e60a6a6de5dca1dfce1cdd2596f02a2a470a1c41dbd","schema_version":"1.0","event_id":"sha256:fbcf2439dac459b530991e60a6a6de5dca1dfce1cdd2596f02a2a470a1c41dbd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GBUNSHA6Z624FFVSX5UXE3GPH3/bundle.json","state_url":"https://pith.science/pith/GBUNSHA6Z624FFVSX5UXE3GPH3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GBUNSHA6Z624FFVSX5UXE3GPH3/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":"2026-08-17T07:38:33Z","links":{"resolver":"https://pith.science/pith/GBUNSHA6Z624FFVSX5UXE3GPH3","bundle":"https://pith.science/pith/GBUNSHA6Z624FFVSX5UXE3GPH3/bundle.json","state":"https://pith.science/pith/GBUNSHA6Z624FFVSX5UXE3GPH3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GBUNSHA6Z624FFVSX5UXE3GPH3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:GBUNSHA6Z624FFVSX5UXE3GPH3","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":"801d6042fe0c291a078451fb64a3b6ad3d9af077f430765840675bba12cf9f60","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-02-17T09:05:10Z","title_canon_sha256":"ee2a12f58be48ffdf22bf4e87bd18db8690821b4205f0eaa541d421f5c96391a"},"schema_version":"1.0","source":{"id":"2202.08526","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2202.08526","created_at":"2026-07-05T04:55:50Z"},{"alias_kind":"arxiv_version","alias_value":"2202.08526v1","created_at":"2026-07-05T04:55:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.08526","created_at":"2026-07-05T04:55:50Z"},{"alias_kind":"pith_short_12","alias_value":"GBUNSHA6Z624","created_at":"2026-07-05T04:55:50Z"},{"alias_kind":"pith_short_16","alias_value":"GBUNSHA6Z624FFVS","created_at":"2026-07-05T04:55:50Z"},{"alias_kind":"pith_short_8","alias_value":"GBUNSHA6","created_at":"2026-07-05T04:55:50Z"}],"graph_snapshots":[{"event_id":"sha256:fbcf2439dac459b530991e60a6a6de5dca1dfce1cdd2596f02a2a470a1c41dbd","target":"graph","created_at":"2026-07-05T04:55:50Z","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/2202.08526/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Generative models can be used to synthesize 3D objects of high quality and diversity. However, there is typically no control over the properties of the generated object.This paper proposes a novel generative adversarial network (GAN) setup that generates 3D point cloud shapes conditioned on a continuous parameter. In an exemplary application, we use this to guide the generative process to create a 3D object with a custom-fit shape. We formulate this generation process in a multi-task setting by using the concept of auxiliary classifier GANs. Further, we propose to sample the generator label in","authors_text":"Andre B\\\"uhler, David Peter, Fabian B. Flohr, J. Marius Z\\\"ollner, Larissa T. Triess","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-02-17T09:05:10Z","title":"Point Cloud Generation with Continuous Conditioning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.08526","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":"sha256:5fa97058d237b6e30207b3fce2b41dc72d81d688df1d2ec12dcc3be701bced38","target":"record","created_at":"2026-07-05T04:55:50Z","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":"801d6042fe0c291a078451fb64a3b6ad3d9af077f430765840675bba12cf9f60","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-02-17T09:05:10Z","title_canon_sha256":"ee2a12f58be48ffdf22bf4e87bd18db8690821b4205f0eaa541d421f5c96391a"},"schema_version":"1.0","source":{"id":"2202.08526","kind":"arxiv","version":1}},"canonical_sha256":"3068d91c1ecfb5c296b2bf69726ccf3eecf7c7c12c76a9fdbbbfa3f0faf2b293","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3068d91c1ecfb5c296b2bf69726ccf3eecf7c7c12c76a9fdbbbfa3f0faf2b293","first_computed_at":"2026-07-05T04:55:50.959664Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:55:50.959664Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kUljgaxmBMJyqPBuT4WX7zHgWugR0upP9Xin77ASc3fiXQRvPlO8QcSLhryF+FimgxFma96Yq0O7W4qrosZeBg==","signature_status":"signed_v1","signed_at":"2026-07-05T04:55:50.960577Z","signed_message":"canonical_sha256_bytes"},"source_id":"2202.08526","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5fa97058d237b6e30207b3fce2b41dc72d81d688df1d2ec12dcc3be701bced38","sha256:fbcf2439dac459b530991e60a6a6de5dca1dfce1cdd2596f02a2a470a1c41dbd"],"state_sha256":"17e4b387db8c2ec66828a920cd12d9388b8e90789161714feda6f367d9326f59"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zEZwViBL7OwEbY+aXjiVPfQDTlwejUy6qimlNk0870NShcPYFsdMJqaUOAvJ3Bw26cGJGx87YsGZtCpO1TChCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T07:38:33.940507Z","bundle_sha256":"b0715b41f479bf76b84a0cecbb0ac203e1492a41f61639da40da726dc1dea70e"}}