activity
20172021
most citedBT-Nets: Simplifying Deep Neural Networks via Block Term Decomposition

12 citations · 26 across the 5 of their papers we have counts for

collaborators

6 papers

eess.IV2021★ 10 cited

Advances In Video Compression System Using Deep Neural Network: A Review And Case Studies

Dandan Ding, Zhan Ma, Di Chen +3

Significant advances in video compression system have been made in the past several decades to satisfy the nearly exponential growth of Internet-scale video traffic. From the appli…

eess.IV2019

Convolutional Neural Networks Based Texture Modeling For AV1

Di Chen, Chichen Fu, Zoe Liu +1

Modern video codecs including the newly developed AOMedia Video 1 (AV1) utilize hybrid coding techniques to remove spatial and temporal redundancy. However, efficient exploitation…

eess.IV2018★ 2 cited

AV1 Video Coding Using Texture Analysis With Convolutional Neural Networks

Di Chen, Chichen Fu, Fengqing Zhu

Modern video codecs including the newly developed AOM/AV1 utilize hybrid coding techniques to remove spatial and temporal redundancy. However, efficient exploitation of statistical…

eess.IV2018

Multi-Reference Video Coding Using Stillness Detection

Di Chen, Zoe Liu, Yaowu Xu +2

Encoders of AOM/AV1 codec consider an input video sequence as succession of frames grouped in Golden-Frame (GF) groups. The coding structure of a GF group is fixed with a given GF…

cs.CV2018★ 2 cited

Texture Segmentation Based Video Compression Using Convolutional Neural Networks

Chichen Fu, Di Chen, Edward J. Delp +2

There has been a growing interest in using different approaches to improve the coding efficiency of modern video codec in recent years as demand for web-based video consumption inc…

stat.ML2017★ 12 cited

BT-Nets: Simplifying Deep Neural Networks via Block Term Decomposition

Guangxi Li, Jinmian Ye, Haiqin Yang +3

Recently, deep neural networks (DNNs) have been regarded as the state-of-the-art classification methods in a wide range of applications, especially in image classification. Despite…