Kernel Density Network for Quantifying Regression Uncertainty in Face Alignment
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[1] A. Weigend,et al. Estimating the mean and variance of the target probability distribution , 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).
[2] Alexander J. Smola,et al. Heteroscedastic Gaussian process regression , 2005, ICML.
[3] Jonathan Tompson,et al. Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation , 2014, NIPS.
[4] Trevor Darrell,et al. Fully convolutional networks for semantic segmentation , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[5] Jia Deng,et al. Stacked Hourglass Networks for Human Pose Estimation , 2016, ECCV.
[6] Georgios Tzimiropoulos,et al. How Far are We from Solving the 2D & 3D Face Alignment Problem? (and a Dataset of 230,000 3D Facial Landmarks) , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[7] Alex Kendall,et al. What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? , 2017, NIPS.
[8] Shiguang Shan,et al. Mean-Variance Loss for Deep Age Estimation from a Face , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.