This repository implements MixNMatch, a CVPR 2020 generative model that learns disentangled representations of images by separating pose, background, shape, and color factors. The model uses adversarial training to encode images into separate latent spaces for each factor and a generator to synthesize new images by recombining arbitrary factor codes. Pretrained models are provided for fine-grained domains including birds, dogs, and cars.