Lightweight head pose estimation without keypoints based on multi-scale lightweight neural network
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Software
Link
https://link.springer.com/content/pdf/10.1007/s00371-023-02781-6.pdf
Reference45 articles.
1. Khan, K., Khan, R.U., Leonardi, R., et al.: Head pose estimation: a survey of the last ten years[J]. Signal Process.: Image Commun. 99, 116479 (2021)
2. Asad S, Mooney B, Ahmad I, et al.: Object detection and sensory feedback techniques in building smart cane for the visually impaired: an overview[C]. Proceedings of the 13th ACM International Conference on PErvasive Technologies Related to Assistive Environments. 2020: 1–7.
3. Chang F J, Tuan Tran A, Hassner T, et al.: Faceposenet: Making a case for landmark-free face alignment[C]. Proceedings of the IEEE International Conference on Computer Vision Workshops. 2017: 1599–1608.
4. Lee S, Saitoh T.: Head pose estimation using convolutional neural network[M]. IT Convergence and Security 2017. Springer, Singapore, 2018: 164–171. C.
5. Xu X, Kakadiaris I A.: Joint head pose estimation and face alignment framework using global and local CNN features[C]. 2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017). IEEE, 2017: 642–649.
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