Demo for performing face, age and emotion detection leveraging pretrained networks from research and the capability to import Caffe models in MATLAB.
Note: If your license includes MATLAB Coder and GPU Coder, you will be able to improve inference performance by generating CUDA code (in the form of MEX files) for each of the predict functions. Review README file for instructions.
References to pretrained models:
 Abars, Face Search VGG16, (2018). GitHub repository, https://github.com/abars/FaceSearchVGG16
 Rasmus Rothe, Radu Timofte and Luc Van Gool, (2016). Deep expectation of real and apparent age from a single image without facial landmarks. International Journal of Computer Vision (IJCV).
 Jia, Yangqing, et al., (2014). "Caffe: Convolutional architecture for fast feature embedding." Proceedings of the 22nd ACM international conference on Multimedia. ACM.
 Gil Levi and Tal Hassner, (2015). Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns. Proc. ACM International Conference on Multimodal Interaction (ICMI). https://osnathassner.github.io/talhassner/projects/cnn_emotions/project.html
Lucas García (2019). Face, Age and Emotion Detection (https://www.mathworks.com/matlabcentral/fileexchange/71819-face-age-and-emotion-detection), MATLAB Central File Exchange. Retrieved .