Deep generative cross-modal on-body accelerometer data synthesis from videos

Author:

Zhang Shibo1,Alshurafa Nabil1

Affiliation:

1. Northwestern University

Publisher

ACM

Cited by 18 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. IMUGPT 2.0: Language-Based Cross Modality Transfer for Sensor-Based Human Activity Recognition;Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies;2024-08-22

2. Advances in AI: Employing Deep Generative Models for the Creation of Synthetic Healthcare Datasets to Improve Predictive Analytics;2023 International Conference on Communication, Security and Artificial Intelligence (ICCSAI);2023-11-23

3. Jawthenticate: Microphone-free Speech-based Authentication using Jaw Motion and Facial Vibrations;Proceedings of the 21st ACM Conference on Embedded Networked Sensor Systems;2023-11-12

4. SudokuSens: Enhancing Deep Learning Robustness for IoT Sensing Applications using a Generative Approach;Proceedings of the 21st ACM Conference on Embedded Networked Sensor Systems;2023-11-12

5. Synthetic Smartwatch IMU Data Generation from In-the-wild ASL Videos;Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies;2023-06-12

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