297 citations · 859 across the 24 of their papers we have counts for
6 papers · 1 filter
Large-Scale Visual Speech Recognition
Brendan Shillingford, Yannis Assael, Matthew W. Hoffman +12
This work presents a scalable solution to open-vocabulary visual speech recognition. To achieve this, we constructed the largest existing visual speech recognition dataset, consist…
Seq-NMS for Video Object Detection
Wei Han, Pooya Khorrami, Tom Le Paine +6
Video object detection is challenging because objects that are easily detected in one frame may be difficult to detect in another frame within the same clip. Recently, there have b…
How Deep Neural Networks Can Improve Emotion Recognition on Video Data
Pooya Khorrami, Tom Le Paine, Kevin Brady +2
We consider the task of dimensional emotion recognition on video data using deep learning. While several previous methods have shown the benefits of training temporal neural networ…
Do Deep Neural Networks Learn Facial Action Units When Doing Expression Recognition?
Pooya Khorrami, Tom Le Paine, Thomas S. Huang
Despite being the appearance-based classifier of choice in recent years, relatively few works have examined how much convolutional neural networks (CNNs) can improve performance on…
An Analysis of Unsupervised Pre-training in Light of Recent Advances
Tom Le Paine, Pooya Khorrami, Wei Han +1
Convolutional neural networks perform well on object recognition because of a number of recent advances: rectified linear units (ReLUs), data augmentation, dropout, and large label…
GPU Asynchronous Stochastic Gradient Descent to Speed Up Neural Network Training
Thomas Paine, Hailin Jin, Jianchao Yang +2
The ability to train large-scale neural networks has resulted in state-of-the-art performance in many areas of computer vision. These results have largely come from computational b…