The past decade has witnessed the great success of deep learning in many disciplines,
especially in computer vision and image processing. However, deep learning-based video …

Deep learning architectures are now pervasive and filled almost all applications under
image processing, computer vision, and biometrics. The attractive property of feature …

This paper develops a unified framework for image-to-image translation based on
conditional diffusion models and evaluates this framework on four challenging image-to …

Blind face restoration usually relies on facial priors, such as facial geometry prior or
reference prior, to restore realistic and faithful details. However, very low-quality inputs …

We extensively study how to combine Generative Adversarial Networks and learned
compression to obtain a state-of-the-art generative lossy compression system. In particular …

We present a learned image compression system based on GANs, operating at extremely
low bitrates. Our proposed framework combines an encoder, decoder/generator and a multi …

Remote photoplethysmography (rPPG), which aims at measuring heart activities without any
contact, has great potential in many applications (eg, remote healthcare). Existing rPPG …

The generative adversarial network (GAN) framework has emerged as a powerful tool for
various image and video synthesis tasks, allowing the synthesis of visual content in an …

Lossy compression algorithms are typically designed and analyzed through the lens of
Shannon's rate-distortion theory, where the goal is to achieve the lowest possible distortion …

Video coding, which targets to compress and reconstruct the whole frame, and feature
compression, which only preserves and transmits the most critical information, stand at two …