Recently, learned image compression techniques have achieved remarkable performance,
even surpassing the best manually designed lossy image coders. They are promising to be …

The emerging conditional coding-based neural video codec (NVC) shows superiority over
commonly-used residual coding-based codec and the latest NVC already claims to …

Entropy modeling is a key component for high-performance image compression algorithms.
Recent developments in autoregressive context modeling helped learning-based methods …

Artificial intelligence represents a new frontier in human medicine that could save more lives
and reduce the costs, thereby increasing accessibility. As a consequence, the rate of …

Natural image compression has been greatly improved in the deep learning era. However,
the compression performance will be heavily degraded if the pretrained encoder is directly …

Content-adaptive compression is crucial for enhancing the adaptability of the pre-trained
neural codec for various contents. Though, its application in neural video compression …

Video coding that pursues the highest compression efficiency is the art of computing for rate-
distortion optimization. The optimization has been approached in different ways, exemplified …

In this paper, we consider the problem of bit allocation in Neural Video Compression (NVC).
First, we reveal a fundamental relationship between bit allocation in NVC and Semi …

Recently, machine learning-based image compression has attracted increasing interests
and is approaching the state-of-the-art compression ratio. But unlike traditional codec, it …

Abstract Learning-based Neural Video Codecs (NVCs) have emerged as a compelling
alternative to standard video codecs, demonstrating promising performance, and simple and …