{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:LYB3YLP55C4H2P5OPPUOHORUGG","short_pith_number":"pith:LYB3YLP5","canonical_record":{"source":{"id":"2002.10876","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-02-25T14:25:01Z","cross_cats_sorted":[],"title_canon_sha256":"0f95b37b733cbb05e6a1977f3671c2f68e6680fc9fa90246faa7e10115ef7dcf","abstract_canon_sha256":"0faeaabfc26e8fced3bed5193acc1785cc941b66c6f2056bfd3f1b6d28c5bd19"},"schema_version":"1.0"},"canonical_sha256":"5e03bc2dfde8b87d3fae7be8e3ba3431971510d3f98e327c6c69278c59469a02","source":{"kind":"arxiv","id":"2002.10876","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.10876","created_at":"2026-07-05T00:49:26Z"},{"alias_kind":"arxiv_version","alias_value":"2002.10876v2","created_at":"2026-07-05T00:49:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.10876","created_at":"2026-07-05T00:49:26Z"},{"alias_kind":"pith_short_12","alias_value":"LYB3YLP55C4H","created_at":"2026-07-05T00:49:26Z"},{"alias_kind":"pith_short_16","alias_value":"LYB3YLP55C4H2P5O","created_at":"2026-07-05T00:49:26Z"},{"alias_kind":"pith_short_8","alias_value":"LYB3YLP5","created_at":"2026-07-05T00:49:26Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:LYB3YLP55C4H2P5OPPUOHORUGG","target":"record","payload":{"canonical_record":{"source":{"id":"2002.10876","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-02-25T14:25:01Z","cross_cats_sorted":[],"title_canon_sha256":"0f95b37b733cbb05e6a1977f3671c2f68e6680fc9fa90246faa7e10115ef7dcf","abstract_canon_sha256":"0faeaabfc26e8fced3bed5193acc1785cc941b66c6f2056bfd3f1b6d28c5bd19"},"schema_version":"1.0"},"canonical_sha256":"5e03bc2dfde8b87d3fae7be8e3ba3431971510d3f98e327c6c69278c59469a02","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:49:26.794406Z","signature_b64":"+tIVk9RqmdNnA9xYoy9Gr9tC6g94002VWFm+DXftdHOnuld2icjS+JPa8o6HVG+2bOTmfN2Mzdq/BOO/LBu6Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5e03bc2dfde8b87d3fae7be8e3ba3431971510d3f98e327c6c69278c59469a02","last_reissued_at":"2026-07-05T00:49:26.794009Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:49:26.794009Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2002.10876","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:49:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JDqYtN8AOj+y9FOVZ0j133X+SR3q4HrtYBv03jOA2+Q50cUNWjhgerzL8hd7lwUT1VC79hfJcHEEC38GufK9Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T13:41:16.564406Z"},"content_sha256":"d968dd5dfe57871dfe0de607da0c342befc45395735c74d8817333499cc63f5a","schema_version":"1.0","event_id":"sha256:d968dd5dfe57871dfe0de607da0c342befc45395735c74d8817333499cc63f5a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:LYB3YLP55C4H2P5OPPUOHORUGG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PointAugment: an Auto-Augmentation Framework for Point Cloud Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chi-Wing Fu, Pheng-Ann Heng, Ruihui Li, Xianzhi Li","submitted_at":"2020-02-25T14:25:01Z","abstract_excerpt":"We present PointAugment, a new auto-augmentation framework that automatically optimizes and augments point cloud samples to enrich the data diversity when we train a classification network. Different from existing auto-augmentation methods for 2D images, PointAugment is sample-aware and takes an adversarial learning strategy to jointly optimize an augmentor network and a classifier network, such that the augmentor can learn to produce augmented samples that best fit the classifier. Moreover, we formulate a learnable point augmentation function with a shape-wise transformation and a point-wise "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.10876","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2002.10876/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":"2026-07-05T00:49:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ba1UEisa+HqVqWzw7Tm4ZnRFG1VnY5t7A+yWRc5rZULEVJ3qM5bPowqyVhsrHk9spncEdcfPdsEuuZgXfp0GCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T13:41:16.565008Z"},"content_sha256":"984102bfa4047ed3481c6a393a2cbc6f6269b4cc246fffff9ebc59b67a3598ac","schema_version":"1.0","event_id":"sha256:984102bfa4047ed3481c6a393a2cbc6f6269b4cc246fffff9ebc59b67a3598ac"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LYB3YLP55C4H2P5OPPUOHORUGG/bundle.json","state_url":"https://pith.science/pith/LYB3YLP55C4H2P5OPPUOHORUGG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LYB3YLP55C4H2P5OPPUOHORUGG/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":"2026-08-04T13:41:16Z","links":{"resolver":"https://pith.science/pith/LYB3YLP55C4H2P5OPPUOHORUGG","bundle":"https://pith.science/pith/LYB3YLP55C4H2P5OPPUOHORUGG/bundle.json","state":"https://pith.science/pith/LYB3YLP55C4H2P5OPPUOHORUGG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LYB3YLP55C4H2P5OPPUOHORUGG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:LYB3YLP55C4H2P5OPPUOHORUGG","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":"0faeaabfc26e8fced3bed5193acc1785cc941b66c6f2056bfd3f1b6d28c5bd19","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-02-25T14:25:01Z","title_canon_sha256":"0f95b37b733cbb05e6a1977f3671c2f68e6680fc9fa90246faa7e10115ef7dcf"},"schema_version":"1.0","source":{"id":"2002.10876","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.10876","created_at":"2026-07-05T00:49:26Z"},{"alias_kind":"arxiv_version","alias_value":"2002.10876v2","created_at":"2026-07-05T00:49:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.10876","created_at":"2026-07-05T00:49:26Z"},{"alias_kind":"pith_short_12","alias_value":"LYB3YLP55C4H","created_at":"2026-07-05T00:49:26Z"},{"alias_kind":"pith_short_16","alias_value":"LYB3YLP55C4H2P5O","created_at":"2026-07-05T00:49:26Z"},{"alias_kind":"pith_short_8","alias_value":"LYB3YLP5","created_at":"2026-07-05T00:49:26Z"}],"graph_snapshots":[{"event_id":"sha256:984102bfa4047ed3481c6a393a2cbc6f6269b4cc246fffff9ebc59b67a3598ac","target":"graph","created_at":"2026-07-05T00:49:26Z","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/2002.10876/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present PointAugment, a new auto-augmentation framework that automatically optimizes and augments point cloud samples to enrich the data diversity when we train a classification network. Different from existing auto-augmentation methods for 2D images, PointAugment is sample-aware and takes an adversarial learning strategy to jointly optimize an augmentor network and a classifier network, such that the augmentor can learn to produce augmented samples that best fit the classifier. Moreover, we formulate a learnable point augmentation function with a shape-wise transformation and a point-wise ","authors_text":"Chi-Wing Fu, Pheng-Ann Heng, Ruihui Li, Xianzhi Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-02-25T14:25:01Z","title":"PointAugment: an Auto-Augmentation Framework for Point Cloud Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.10876","kind":"arxiv","version":2},"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:d968dd5dfe57871dfe0de607da0c342befc45395735c74d8817333499cc63f5a","target":"record","created_at":"2026-07-05T00:49:26Z","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":"0faeaabfc26e8fced3bed5193acc1785cc941b66c6f2056bfd3f1b6d28c5bd19","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-02-25T14:25:01Z","title_canon_sha256":"0f95b37b733cbb05e6a1977f3671c2f68e6680fc9fa90246faa7e10115ef7dcf"},"schema_version":"1.0","source":{"id":"2002.10876","kind":"arxiv","version":2}},"canonical_sha256":"5e03bc2dfde8b87d3fae7be8e3ba3431971510d3f98e327c6c69278c59469a02","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5e03bc2dfde8b87d3fae7be8e3ba3431971510d3f98e327c6c69278c59469a02","first_computed_at":"2026-07-05T00:49:26.794009Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:49:26.794009Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+tIVk9RqmdNnA9xYoy9Gr9tC6g94002VWFm+DXftdHOnuld2icjS+JPa8o6HVG+2bOTmfN2Mzdq/BOO/LBu6Bw==","signature_status":"signed_v1","signed_at":"2026-07-05T00:49:26.794406Z","signed_message":"canonical_sha256_bytes"},"source_id":"2002.10876","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d968dd5dfe57871dfe0de607da0c342befc45395735c74d8817333499cc63f5a","sha256:984102bfa4047ed3481c6a393a2cbc6f6269b4cc246fffff9ebc59b67a3598ac"],"state_sha256":"3642cedb977ebc11257350c5bf71baccec282ea0361ea5f27b56885ee4aac4c5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mQRO0XikySIjilX8B/6lbs0S15aacwYs7Cf2l13rnXszk2F5sXaZUGtCMLzn6GtflzrtscmiEKxVZZ833dEjCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T13:41:16.568663Z","bundle_sha256":"329b7bc6d31cd1be165a4a7a178a6b34c40804e73469a27cbdfe3b199ca09345"}}