Deep Motion Masking for Secure, Usable, and Scalable Real-Time Anonymization of Ecological Virtual Reality Motion Data-Reference-Cited by-同舟云学术

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Deep Motion Masking for Secure, Usable, and Scalable Real-Time Anonymization of Ecological Virtual Reality Motion Data

Published:2024-03-16 Issue: Volume: Page:493-500
ISSN:
Container-title:2024 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)
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Author:

Nair Vivek¹,Guo Wenbo²,O'Brien James F.¹,Rosenberg Louis³,Song Dawn¹

Affiliation:

1. UC Berkeley

2. Purdue University

3. Unanimous AI

Funder

National Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10536145/10536146/10536254.pdf?arnumber=10536254

Reference40 articles.

1. Malicious Design in AIVR, Falsehood and Cybersecurity-oriented Immersive Defenses

2. Apple Vision Pro: Comments in Healthcare

3. Siamese Neural Networks: An Overview

4. Recognizing friends by their walk: Gait perception without familiarity cues

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Effect of Data Degradation on Motion Re-Identification;2024 IEEE 25th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM);2024-06-04

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