With the rapid advancements of the text-to-image generative model, AI-generated images
(AGIs) have been widely applied to entertainment, education, social media, etc. However …

Several recent studies advocate the use of spectral discriminators, which evaluate the
Fourier spectra of images for generative modeling. However, the effectiveness of the …

Traditional deep neural network (DNN)-based image quality assessment (IQA) models
leverage convolutional neural networks (CNN) or Transformer to learn the quality-aware …

Recently, generative adversarial networks (GANs) have been investigated since 2014, and
many algorithmic solutions have been suggested for them. GAN have recently become a …

Limited by storage conditions, the degradation of old photos exhibits complex and diverse
features. Existing image restoration methods heavily rely on features extracted from a single …

Neural network-based image coding has been developing rapidly since its birth. Until 2022,
its performance has surpassed that of the best-performing traditional image coding …

The large‐scale integration of new energy generation into the power transmission network
introduces uncertainty and fluctuations, posing a threat to the secure operation of the …

The past few years have witnessed a great success in applying deep learning to enhance
the perceptual quality of compressed video. These methods usually perform frame-by-frame …

Upscaling images typically depends on facial features, such as facial geometry details or
references, to rebuild reasonable details. The low-quality input images cannot offer accurate …

Mainstream image/video coding standards, exemplified by the state-of-the-art H. 266/VVC,
AVS3, and AV1, follow the block-based hybrid coding framework. Due to the block-based …