EMOCA is a deep learning-based system for monocular face capture and animation. It takes a single face image as input and produces a 3D reconstruction including shape, expression, and detailed geometric displacements. The method uses a deep neural network trained on facial imagery to regress 3D face model parameters, achieving robust reconstruction even for highly emotional expressions captured in the wild. The implementation relies on PyTorch and PyTorch Lightning for model training and inference.