Computer Vision, Gans, Generative Adversarial, Generative Mo, Deep Learning.
is how the autoencoder network looks. This network is trained in such a way that the features (z) can be used to reconstruct the original input data (x). If the output (Ẋ) is different from the input (x), the L2 loss penalizes it and helps to reconstruct the input data. Now, how can we generate new