Disentangled representation learning aims at obtaining an independent latent
representation without supervisory signals. However, the independence of a representation …

Disentanglement learning aims to separate explanatory factors of variation so that different
attributes of the data can be well characterized and isolated, which promotes efficient …

Efforts have been made in understanding the latent representations constructed by
generative adversarial networks (GANs), which facilitate the efficient learning and …

The use of Generative Adversarial Networks (GANs) has led to significant advancements in
the field of compositional image synthesis. In particular, recent progress has focused on …

The modern world contains a significant number of applications based on computer vision,
in which human-computer interaction plays a crucial role, pose estimation of the hand is a …