activity
20152017
most citedAn All-in-One Network for Dehazing and Beyond

137 citations · 204 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CV20175 cited

Predicting Depression Severity by Multi-Modal Feature Engineering and Fusion

Aven Samareh, Yan Jin, Zhangyang Wang +2

We present our preliminary work to determine if patient's vocal acoustic, linguistic, and facial patterns could predict clinical ratings of depression severity, namely Patient Heal…

cs.CV201724 cited

End-to-End United Video Dehazing and Detection

Boyi Li, Xiulian Peng, Zhangyang Wang +2

The recent development of CNN-based image dehazing has revealed the effectiveness of end-to-end modeling. However, extending the idea to end-to-end video dehazing has not been expl…

cs.CV20176 cited

Robust Emotion Recognition from Low Quality and Low Bit Rate Video: A Deep Learning Approach

Bowen Cheng, Zhangyang Wang, Zhaobin Zhang +5

Emotion recognition from facial expressions is tremendously useful, especially when coupled with smart devices and wireless multimedia applications. However, the inadequate network…

cs.CV2017137 cited

An All-in-One Network for Dehazing and Beyond

Boyi Li, Xiulian Peng, Zhangyang Wang +2

This paper proposes an image dehazing model built with a convolutional neural network (CNN), called All-in-One Dehazing Network (AOD-Net). It is designed based on a re-formulated a…

cs.LG2016

Learning A Deep Encoder for Hashing

Zhangyang Wang, Yingzhen Yang, Shiyu Chang +2

We investigate the -constrained representation which demonstrates robustness to quantization errors, utilizing the tool of deep learning. Based on the Alternating Dire…

cs.CV20159 cited

DeepFont: Identify Your Font from An Image

Zhangyang Wang, Jianchao Yang, Hailin Jin +4

As font is one of the core design concepts, automatic font identification and similar font suggestion from an image or photo has been on the wish list of many designers. We study t…