597 citations · 2.3k across the 106 of their papers we have counts for
7 papers · 1 filter
Enhanced Attacks on Defensively Distilled Deep Neural Networks
Yujia Liu, Weiming Zhang, Shaohua Li +1
Deep neural networks (DNNs) have achieved tremendous success in many tasks of machine learning, such as the image classification. Unfortunately, researchers have shown that DNNs ar…
Exfiltration of Data from Air-gapped Networks via Unmodulated LED Status Indicators
Zheng Zhou, Weiming Zhang, Zichong Yang +1
The light-emitting diode(LED) is widely used as an indicator on the information device. Early in 2002, Loughry et al studied the exfiltration of LED indicators and found the kind o…
Online Multi-Object Tracking Using CNN-based Single Object Tracker with Spatial-Temporal Attention Mechanism
Qi Chu, Wanli Ouyang, Hongsheng Li +3
In this paper, we propose a CNN-based framework for online MOT. This framework utilizes the merits of single object trackers in adapting appearance models and searching for target…
Dual Supervised Learning
Yingce Xia, Tao Qin, Wei Chen +3
Many supervised learning tasks are emerged in dual forms, e.g., English-to-French translation vs. French-to-English translation, speech recognition vs. text to speech, and image cl…
Learning Spatial Regularization with Image-level Supervisions for Multi-label Image Classification
Feng Zhu, Hongsheng Li, Wanli Ouyang +2
Multi-label image classification is a fundamental but challenging task in computer vision. Great progress has been achieved by exploiting semantic relations between labels in recen…
Coherent Online Video Style Transfer
Dongdong Chen, Jing Liao, Lu Yuan +2
Training a feed-forward network for fast neural style transfer of images is proven to be successful. However, the naive extension to process video frame by frame is prone to produc…
StyleBank: An Explicit Representation for Neural Image Style Transfer
Dongdong Chen, Lu Yuan, Jing Liao +2
We propose StyleBank, which is composed of multiple convolution filter banks and each filter bank explicitly represents one style, for neural image style transfer. To transfer an i…