Action Unit Recognition: Leveraging Weak Supervision with Large Loss Rejection

Author:

Enabor Oseluole,Vadapalli Hima

Publisher

Springer Nature Switzerland

Reference21 articles.

1. Almaev, T., Martinez, B., Valstar, M.: Learning to transfer: transferring latent task structures and its application to person-specific facial action unit detection. In: Proceedings of the IEEE International Conference on Computer Vision (ICCV), December 2015

2. Chen, J., Wang, C., Wang, K., Liu, M.: Computational efficient deep neural network with difference attention maps for facial action unit detection. arXiv preprint arXiv:2011.12082 (2020)

3. Granger, E., Cardinal, P., et al.: Weakly supervised learning for facial behavior analysis: a review. arXiv preprint arXiv:2101.09858 (2021)

4. Kim, Y., Kim, J.M., Akata, Z., Lee, J.: Large loss matters in weakly supervised multi-label classification. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 14156–14165 (2022)

5. Lee, D.-H., et al.: Pseudo-label: the simple and efficient semi-supervised learning method for deep neural networks. In: Workshop on Challenges in Representation Learning, ICML, vol. 3, p. 896 (2013)

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