Latent code for unsupervised domain adaptation

A pre-trained source encoder generates a source encoder representation for each image of a labeled set of source images from a source domain. A target encoder generates a target encoder representation for each image of an unlabeled set of target images from a target domain. A generative adversarial network outputs a first prediction indicating whether each of the source encoder representations and each of the target encoder representations originate from the source domain or the target domain. The generative adversarial network outputs a second prediction of the latent code for each of the source encoder representations and each of the target encoder representations. The target encoder and the generative adversarial network are trained by repeatedly updating parameters of the target encoder and the generative adversarial network until one or more predetermined stopping conditions occur.