Downsampling operations such as max pooling or strided convolution are ubiquitously
utilized in Convolutional Neural Networks (CNNs) to aggregate local features, enlarge …

Built on deep networks, end-to-end optimized image compression has made impressive
progress in the past few years. Previous studies usually adopt a compressive auto-encoder …

Image denoising aims to restore a clean image from an observed noisy one. Model-based
image denoising approaches can achieve good generalization ability over different noise …

Using high-fidelity image compression makes it possible to transmit remote-sensing images
in real-time. Nevertheless, existing lossy remote-sensing image compression (RSIC) …

Image/video compression and communication need to serve both human vision and
machine vision. To address this need, we propose a scalable image compression solution …

Global average pooling (GAP) plays an important role in traditional channel attention.
However, there is the disadvantage of insufficient information to use the result of GAP as the …

Learned image compression methods have achieved satisfactory results in recent years.
However, existing methods are typically designed for RGB format, which are not suitable for …

Video compression performance is closely related to the accuracy of inter prediction. It tends
to be difficult to obtain accurate inter prediction for the local video regions with inconsistent …

Volumetric medical images are extensively employed in medical diagnosis, treatment, and
research, necessitating a significant demand for coding. Currently, JP3D and HEVC are the …

This paper provides a survey of the latest developments in visual signal coding and
processing with generative models. Specifically, our focus is on presenting the advancement …