most citedNeural Video Compression using Spatio-Temporal Priors

10 citations · 21 across the 3 of their papers we have counts for

collaborators

5 papers

eess.IV20193 cited

Learned Video Compression via Joint Spatial-Temporal Correlation Exploration

Haojie Liu, Han shen, Lichao Huang +3

Traditional video compression technologies have been developed over decades in pursuit of higher coding efficiency. Efficient temporal information representation plays a key role i…

eess.IV2019

Extreme Image Coding via Multiscale Autoencoders With Generative Adversarial Optimization

Chao Huang, Haojie Liu, Tong Chen +2

We propose a MultiScale AutoEncoder(MSAE) based extreme image compression framework to offer visually pleasing reconstruction at a very low bitrate. Our method leverages the "prior…

eess.IV20198 cited

Gated Context Model with Embedded Priors for Deep Image Compression

Haojie Liu, Tong Chen, Peiyao Guo +2

A deep image compression scheme is proposed in this paper, offering the state-of-the-art compression efficiency, against the traditional JPEG, JPEG2000, BPG and those popular learn…

eess.IV201910 cited

Neural Video Compression using Spatio-Temporal Priors

Haojie Liu, Tong Chen, Ming Lu +2

The pursuit of higher compression efficiency continuously drives the advances of video coding technologies. Fundamentally, we wish to find better "predictions" or "priors" that are…

eess.IV2018

Deep Image Compression via End-to-End Learning

Haojie Liu, Tong Chen, Qiu Shen +2

We present a lossy image compression method based on deep convolutional neural networks (CNNs), which outperforms the existing BPG, WebP, JPEG2000 and JPEG as measured via multi-sc…