We address the problem of single photo age progression and regression—the prediction of
how a person might look in the future, or how they looked in the past. Most existing aging …

A deep facial attribute editing model strives to meet two requirements:(1) attribute
correctness--the target attribute should correctly appear on the edited face image;(2) …

Counterfactual explanations have shown promising results as a post-hoc framework to make
image classifiers more explainable. In this paper, we propose DiME, a method allowing the …

Image generation relies on massive training data that can hardly produce diverse images of
an unseen category according to a few examples. In this paper, we address this dilemma by …

In human-centric content generation the pre-trained text-to-image models struggle to
produce user-wanted portrait images which retain the identity of individuals while exhibiting …

Semantic image synthesis, translating semantic layouts to photo-realistic images, is a one-to-
many mapping problem. Though impressive progress has been recently made, diverse …

In this paper, we focus on the semantic image synthesis task that aims at transferring
semantic label maps to photo-realistic images. Existing methods lack effective semantic …

Recently, Generative Adversarial Networks (GANs) have been widely used for portrait image
generation. However, in the latent space learned by GANs, different attributes, such as pose …

Recently, deep learning technique has been widely employed to deal with face super-
resolution (FSR) problem. It aims to predict the nonlinear relationship between the low …

Interactive image segmentation aims to segment the target from the background with the
manual guidance, which takes as input multimodal data such as images, clicks, scribbles …