by Christy Koh, November 2021
This project aims to use neural networks to automatically detect facial keypoints.
This first part uses the IMM Face Database to train a toy model for nose tip detection. Pictured below are three sampled images from the dataloader, visualized with ground-truth nose tip keypoints.
For this model, I used 3 convolutional layers and 2 fully-connected layers, with ReLu and max-pooling after each convolutional layer.
The loss function was a simple Mean-Squared Error (nn.MSELoss) computation, and we used the Adam gradient-based optimizer to update the