Existing methods mainly extract the text information from only one sentence to represent an image and the text representation effects the quality of the generated image well.
To transfer knowledge between discriminators, we design a multi-level discriminant knowledge distillation from the source discriminator to the target discriminator on both the real and fake samples.
Formulated as a conditional generation problem, face animation aims at synthesizing continuous face images from a single source image driven by a set of conditional face motion.
As a challenging task, unsupervised person ReID aims to match the same identity with query images which does not require any labeled information.
Different from many other attributes, facial expression can change in a continuous way, and therefore, a slight semantic change of input should also lead to the output fluctuation limited in a small scale.