PaperarXiv:2111.12082
PhysFormer: Facial Video-based Physiological Measurement with Temporal Difference Transformer
CVPR 2022
Open codeLicence: MIT
TL;DR
PhysFormer is an end-to-end video transformer for remote PPG from face video. Temporal-difference transformers aggregate local and global spatio-temporal features, with label-distribution learning and a frequency-domain constraint. CVPR 2022, pp. 4176–4186 (DOI 10.1109/cvpr52688.2022.00415). The paper points to code at https://github.com/ZitongYu/PhysFormer, which is released under MIT.
- Authors: Zitong Yu, Yuming Shen, Jingang Shi, Hengshuang Zhao, Philip Torr, Guoying Zhao
- CVPR 2022, pp. 4176–4186; DOI 10.1109/cvpr52688.2022.00415
- Code: https://github.com/ZitongYu/PhysFormer (MIT)
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APA
Yu, Z., Shen, Y., Shi, J., Zhao, H., Torr, P., & Zhao, G. (2022). PhysFormer: Facial Video-based Physiological Measurement with Temporal Difference Transformer. CVPR 2022. https://doi.org/10.1109/cvpr52688.2022.00415
BibTeX
@inproceedings{yu2022physformer,
title = {{PhysFormer: Facial Video-based Physiological Measurement with Temporal Difference Transformer}},
author = {Yu, Zitong and Shen, Yuming and Shi, Jingang and Zhao, Hengshuang and Torr, Philip and Zhao, Guoying},
year = {2022},
booktitle = {CVPR 2022},
doi = {10.1109/cvpr52688.2022.00415},
eprint = {2111.12082},
archivePrefix = {arXiv}
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