Abstract: One embodiment of the present invention sets forth a technique for performing identity-preserving image generation. The technique includes converting an identity image depicting a facial identity into an identity embedding. The technique further includes generating a combined embedding based on the identity embedding and a diffusion iteration identifier. The technique further includes converting, using a neural network and based on the combined embedding, a first input image that includes first noise into a first predicted image depicting one or more facial features that include one or more first facial identity features, wherein the one or more first facial identity features correspond to one or more respective second facial identity features of the identity image and are based at least on the identity embedding.

Abstract: One embodiment of the present invention sets forth a technique for performing face swapping. The technique includes generating a latent representation of a first facial identity included in an input image. The technique further includes identifying a first identity-specific neural network layer associated with a second facial identity from a plurality of identity-specific neural network layers, wherein each neural network layer included in the plurality of identity-specific neural network layers is associated with a different facial identity. The technique further includes executing the first identity-specific neural network layer and one or more other neural network layers to generate one or more decoder input values corresponding to the latent representation. The technique further includes executing a decoder neural network that converts the one or more decoder input values into an output image depicting the second facial identity.