Lightweight network architecture using difference saliency maps for facial action unit detection
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10489-021-02755-y.pdf
Reference39 articles.
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2. Bosch A, Zisserman A, Munoz X (2007) Representing shape with a spatial pyramid kernel. In: Proceedings of the 6th ACM international conference on image and video retrieval, CIVR ’07, pp 401–408, Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/1282280.1282340
3. Corneanu C, Madadi M, Escalera S (2018) Deep structure inference network for facial action unit recognition. In: Proceedings of the european conference on computer vision (ECCV), pp. 298–313
4. Eleftheriadis S, Rudovic O, Pantic M (2015) Multi-conditional latent variable model for joint facial action unit detection. In: 2015 IEEE international conference on computer vision (ICCV), pp 3792–3800. https://doi.org/10.1109/ICCV.2015.432
5. Friesen E, Ekman P (1978) Facial action coding system: a technique for the measurement of facial movement. Palo Alto 3
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