Category Archives: Deep Learning

Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns

In the last post we talked about age and gender classification from face images using deep convolutional neural networks. In this post we will show a similar approach for emotion recognition from face images that also makes use of a novel image representation based on mapping Local Binary Patterns to a 3D space suitable for finetuning Deep Convolutional Neural Networks [8]:

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Local Binary Patterns (LBP) Mapping

Our method was presented in the following paper:

Gil Levi and Tal Hassner, Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns, Proc. ACM International Conference on Multimodal Interaction (ICMI), Seattle, Nov. 2015

For code, models and examples, please see our project page.

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Deep Learning 101 talk at DevCon 2016

At the recent DevCon conference I had the pleasure of giving an introductory talk to Deep Learning. A short theoretical overview is given following a technical deep dive on how to train deep networks with a few demos, practical examples and tips.

 

The notebook used in the demo is available here and the various deep networks and definition files used to run the demo are available here.

Age and Gender Classification using Deep Convolutional Neural Networks

In the last few posts we mostly talked about binary image descriptors and the previous post in this line of works described our very own LATCH descriptor [1] and presented an evaluation of various binary and floating point image descriptors. In the current post we will shift our attention to the field of Deep Learning and present our work on Age and Gender classification from face image using Deep Convolutional Neural Networks [2].

Example images from the AdienceFaces benchmark

Example images from the AdienceFaces benchmark

Our method was presented in the following paper:

Gil Levi and Tal Hassner, Age and Gender Classification using Convolutional Neural Networks, IEEE Workshop on Analysis and Modeling of Faces and Gestures (AMFG), at the IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Boston, June 2015.

For code, models and examples, please see our project page.

New! Tensor-Flow implementation of our method .

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