{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:YHK4QGLN6PI4S2B4R2WXTN5AL4","short_pith_number":"pith:YHK4QGLN","schema_version":"1.0","canonical_sha256":"c1d5c8196df3d1c9683c8ead79b7a05f0da2c05d35eb2b72e3c19ba530b81c72","source":{"kind":"arxiv","id":"2308.13093","version":2},"attestation_state":"computed","paper":{"title":"EgoBlur: Responsible Innovation in Aria","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Carl Ren, Edward Miller, Guruprasad Somasundaram, Ishita Prasad, Jeff Meissner, Kang Zheng, Luis Pesqueira, Mark Schwesinger, Mingfei Yan, Nikhil Raina, Omkar M Parkhi, Prince Gupta, Richard Newcombe, Sagar Miglani, Steve Saarinen","submitted_at":"2023-08-24T21:36:11Z","abstract_excerpt":"Project Aria pushes the frontiers of Egocentric AI with large-scale real-world data collection using purposely designed glasses with privacy first approach. To protect the privacy of bystanders being recorded by the glasses, our research protocols are designed to ensure recorded video is processed by an AI anonymization model that removes bystander faces and vehicle license plates. Detected face and license plate regions are processed with a Gaussian blur such that these personal identification information (PII) regions are obscured. This process helps to ensure that anonymized versions of the"},"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":"2308.13093","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-08-24T21:36:11Z","cross_cats_sorted":[],"title_canon_sha256":"5ac7fbafdfd6f5f89e2af895516f1146f7867de9c9d32a0cb9c825b6a195d5f8","abstract_canon_sha256":"2b93ebf62af7d3e682aa53367925fa84333060aac94d0d9396ce5716bd7f9d0e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:48:11.041500Z","signature_b64":"ohtYYA8We1VEiZMwr6cU8+mhV1WCSSrOpU6ji/Rl02B0s2fBX6Fri/1U8mlk+Rbh6wWQP1cwDt61Htnjr9nJAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c1d5c8196df3d1c9683c8ead79b7a05f0da2c05d35eb2b72e3c19ba530b81c72","last_reissued_at":"2026-07-05T06:48:11.041071Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:48:11.041071Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"EgoBlur: Responsible Innovation in Aria","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Carl Ren, Edward Miller, Guruprasad Somasundaram, Ishita Prasad, Jeff Meissner, Kang Zheng, Luis Pesqueira, Mark Schwesinger, Mingfei Yan, Nikhil Raina, Omkar M Parkhi, Prince Gupta, Richard Newcombe, Sagar Miglani, Steve Saarinen","submitted_at":"2023-08-24T21:36:11Z","abstract_excerpt":"Project Aria pushes the frontiers of Egocentric AI with large-scale real-world data collection using purposely designed glasses with privacy first approach. To protect the privacy of bystanders being recorded by the glasses, our research protocols are designed to ensure recorded video is processed by an AI anonymization model that removes bystander faces and vehicle license plates. Detected face and license plate regions are processed with a Gaussian blur such that these personal identification information (PII) regions are obscured. This process helps to ensure that anonymized versions of the"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.13093","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/2308.13093/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":"2308.13093","created_at":"2026-07-05T06:48:11.041128+00:00"},{"alias_kind":"arxiv_version","alias_value":"2308.13093v2","created_at":"2026-07-05T06:48:11.041128+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.13093","created_at":"2026-07-05T06:48:11.041128+00:00"},{"alias_kind":"pith_short_12","alias_value":"YHK4QGLN6PI4","created_at":"2026-07-05T06:48:11.041128+00:00"},{"alias_kind":"pith_short_16","alias_value":"YHK4QGLN6PI4S2B4","created_at":"2026-07-05T06:48:11.041128+00:00"},{"alias_kind":"pith_short_8","alias_value":"YHK4QGLN","created_at":"2026-07-05T06:48:11.041128+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":4,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2605.05945","citing_title":"MobileEgo Anywhere: Open Infrastructure for long horizon egocentric data on commodity hardware","ref_index":20,"is_internal_anchor":false},{"citing_arxiv_id":"2410.18717","citing_title":"Low-Latency Video Anonymization for Crowd Anomaly Detection: Privacy Versus Performance","ref_index":11,"is_internal_anchor":false},{"citing_arxiv_id":"2603.27817","citing_title":"Towards Context-Aware Image Anonymization with Multi-Agent Reasoning","ref_index":31,"is_internal_anchor":false},{"citing_arxiv_id":"2604.13315","citing_title":"The Spectrascapes Dataset: Street-view imagery beyond the visible captured using a mobile platform","ref_index":33,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/YHK4QGLN6PI4S2B4R2WXTN5AL4","json":"https://pith.science/pith/YHK4QGLN6PI4S2B4R2WXTN5AL4.json","graph_json":"https://pith.science/api/pith-number/YHK4QGLN6PI4S2B4R2WXTN5AL4/graph.json","events_json":"https://pith.science/api/pith-number/YHK4QGLN6PI4S2B4R2WXTN5AL4/events.json","paper":"https://pith.science/paper/YHK4QGLN"},"agent_actions":{"view_html":"https://pith.science/pith/YHK4QGLN6PI4S2B4R2WXTN5AL4","download_json":"https://pith.science/pith/YHK4QGLN6PI4S2B4R2WXTN5AL4.json","view_paper":"https://pith.science/paper/YHK4QGLN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2308.13093&json=true","fetch_graph":"https://pith.science/api/pith-number/YHK4QGLN6PI4S2B4R2WXTN5AL4/graph.json","fetch_events":"https://pith.science/api/pith-number/YHK4QGLN6PI4S2B4R2WXTN5AL4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YHK4QGLN6PI4S2B4R2WXTN5AL4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YHK4QGLN6PI4S2B4R2WXTN5AL4/action/storage_attestation","attest_author":"https://pith.science/pith/YHK4QGLN6PI4S2B4R2WXTN5AL4/action/author_attestation","sign_citation":"https://pith.science/pith/YHK4QGLN6PI4S2B4R2WXTN5AL4/action/citation_signature","submit_replication":"https://pith.science/pith/YHK4QGLN6PI4S2B4R2WXTN5AL4/action/replication_record"}},"created_at":"2026-07-05T06:48:11.041128+00:00","updated_at":"2026-07-05T06:48:11.041128+00:00"}