Image fusion integrates a series of images acquired from different sensors, eg, infrared and
visible, outputting an image with richer information than either one. Traditional and recent …

In real-world applications, it is often that the collected multi-view data are incomplete, ie,
some views of samples are absent. Existing clustering methods for incomplete multi-view …

Versatile Video Coding (VVC), as the latest standard, significantly improves the coding
efficiency over its predecessor standard High Efficiency Video Coding (HEVC), but at the …

Traditional watermarking algorithms have been extensively studied. As an important type of
watermarking schemes, template-based approaches maintain a very high embedding rate …

In this work, we propose a Wavelet-based Deep Auto Encoder-Decoder Network (WDAED)
based image compression which takes care of the various frequency components present in …

Deep learning provides a great potential for in-loop filtering to improve both coding
efficiency and subjective quality in video coding. State-of-the-art work focuses on network …

The computational time of HEVC encoder is increased mainly because of the hierarchical
quad-tree-based structure, recursive coding units, and the exhaustive prediction search up …

The increase of video content and video resolution drive more exploration of video
compression techniques recently. Meanwhile, learning-based video compression is …

Recently, many researches on convolution neural network (CNN) based in-loop filters have
been proposed to improve coding efficiency. However, most existing CNN based filters tend …

Recently, due to the strength of deep convolutional neural networks (CNN), many CNN-
based image quality assessment (IQA) models have been studied. However, previous CNN …