{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:ZUTTSKVOQ3YTO55ORQPDMYTGHB","short_pith_number":"pith:ZUTTSKVO","schema_version":"1.0","canonical_sha256":"cd27392aae86f13777ae8c1e3662663840814c4014cd6959f4d5ca44095da995","source":{"kind":"arxiv","id":"2502.02247","version":1},"attestation_state":"computed","paper":{"title":"Rotation-Adaptive Point Cloud Domain Generalization via Intricate Orientation Learning","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CV","authors_text":"Bangzhen Liu, Cheng Xu, Chenxi Zheng, Huaidong Zhang, Shengfeng He, Xuemiao Xu","submitted_at":"2025-02-04T11:46:32Z","abstract_excerpt":"The vulnerability of 3D point cloud analysis to unpredictable rotations poses an open yet challenging problem: orientation-aware 3D domain generalization. Cross-domain robustness and adaptability of 3D representations are crucial but not easily achieved through rotation augmentation. Motivated by the inherent advantages of intricate orientations in enhancing generalizability, we propose an innovative rotation-adaptive domain generalization framework for 3D point cloud analysis. Our approach aims to alleviate orientational shifts by leveraging intricate samples in an iterative learning process."},"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":"2502.02247","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2025-02-04T11:46:32Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"151019f998ece5c4434ff635bd31b4cb366e039eb15afbffec6e03c47252c69b","abstract_canon_sha256":"7e80a198e8def87f2ba05244a8bc2fda2107ca2011c79a8a5073c7c825a56a5f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:09:25.974447Z","signature_b64":"0/w3QrT8dyNFZrE17zq40JqymQVFvBMu2W4lLgcVLZl7vR4YeodYSVbdA2+TG6XGZU49MU5cpp5/v6KDwA1eCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cd27392aae86f13777ae8c1e3662663840814c4014cd6959f4d5ca44095da995","last_reissued_at":"2026-07-05T10:09:25.974099Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:09:25.974099Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Rotation-Adaptive Point Cloud Domain Generalization via Intricate Orientation Learning","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CV","authors_text":"Bangzhen Liu, Cheng Xu, Chenxi Zheng, Huaidong Zhang, Shengfeng He, Xuemiao Xu","submitted_at":"2025-02-04T11:46:32Z","abstract_excerpt":"The vulnerability of 3D point cloud analysis to unpredictable rotations poses an open yet challenging problem: orientation-aware 3D domain generalization. Cross-domain robustness and adaptability of 3D representations are crucial but not easily achieved through rotation augmentation. Motivated by the inherent advantages of intricate orientations in enhancing generalizability, we propose an innovative rotation-adaptive domain generalization framework for 3D point cloud analysis. Our approach aims to alleviate orientational shifts by leveraging intricate samples in an iterative learning process."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.02247","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/2502.02247/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":"2502.02247","created_at":"2026-07-05T10:09:25.974154+00:00"},{"alias_kind":"arxiv_version","alias_value":"2502.02247v1","created_at":"2026-07-05T10:09:25.974154+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.02247","created_at":"2026-07-05T10:09:25.974154+00:00"},{"alias_kind":"pith_short_12","alias_value":"ZUTTSKVOQ3YT","created_at":"2026-07-05T10:09:25.974154+00:00"},{"alias_kind":"pith_short_16","alias_value":"ZUTTSKVOQ3YTO55O","created_at":"2026-07-05T10:09:25.974154+00:00"},{"alias_kind":"pith_short_8","alias_value":"ZUTTSKVO","created_at":"2026-07-05T10:09:25.974154+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/ZUTTSKVOQ3YTO55ORQPDMYTGHB","json":"https://pith.science/pith/ZUTTSKVOQ3YTO55ORQPDMYTGHB.json","graph_json":"https://pith.science/api/pith-number/ZUTTSKVOQ3YTO55ORQPDMYTGHB/graph.json","events_json":"https://pith.science/api/pith-number/ZUTTSKVOQ3YTO55ORQPDMYTGHB/events.json","paper":"https://pith.science/paper/ZUTTSKVO"},"agent_actions":{"view_html":"https://pith.science/pith/ZUTTSKVOQ3YTO55ORQPDMYTGHB","download_json":"https://pith.science/pith/ZUTTSKVOQ3YTO55ORQPDMYTGHB.json","view_paper":"https://pith.science/paper/ZUTTSKVO","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2502.02247&json=true","fetch_graph":"https://pith.science/api/pith-number/ZUTTSKVOQ3YTO55ORQPDMYTGHB/graph.json","fetch_events":"https://pith.science/api/pith-number/ZUTTSKVOQ3YTO55ORQPDMYTGHB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ZUTTSKVOQ3YTO55ORQPDMYTGHB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ZUTTSKVOQ3YTO55ORQPDMYTGHB/action/storage_attestation","attest_author":"https://pith.science/pith/ZUTTSKVOQ3YTO55ORQPDMYTGHB/action/author_attestation","sign_citation":"https://pith.science/pith/ZUTTSKVOQ3YTO55ORQPDMYTGHB/action/citation_signature","submit_replication":"https://pith.science/pith/ZUTTSKVOQ3YTO55ORQPDMYTGHB/action/replication_record"}},"created_at":"2026-07-05T10:09:25.974154+00:00","updated_at":"2026-07-05T10:09:25.974154+00:00"}