Disentangling latent representations for image reenactment

An apparatus comprising:

• at least one processor;
• and
• at least one memory including instructions executable by the at least one processor to:
• encode features of a source image to obtain a source appearance encoding that represents inherent attributes of a face in the source image;
• encode features of a target image to obtain a target non-appearance encoding that represents contextual attributes of the target image;
• combine the source appearance encoding and the target non-appearance encoding using a reconstruction network to obtain combined image features, wherein the combined image features comprise a reconstructed vector in a latent space of a generator network;
• and
• generate, using the generator network, a modified target image based on the combined image features, wherein the modified target image includes the inherent attributes of the face in the source image together with the contextual attributes of the target image.

A non-transitory computer readable medium storing code for image processing, the code comprising instructions executable by at least one processor to:

• encode features of a source image to obtain a source appearance encoding that represents inherent attributes of a face in the source image;
• encode features of a target image to obtain a target non-appearance encoding that represents contextual attributes of the target image;
• combine the source appearance encoding and the target non-appearance encoding using a reconstruction network to obtain combined image features, wherein the combined image features comprise a reconstructed vector in a latent space of a generator network;
• and
• generate, using the generator network, a modified target image based on the combined image features, wherein the modified target image includes the inherent attributes of the face in the source image together with the contextual attributes of the target image.