Deep Learning for Computer Vision

Summary

In this chapter, we have understood the problems associated with image captions. We saw a few techniques involving natural language processing and various word2vec models such as GLOVE. We understood several algorithms such as CNN2RNN, metric learning, and combined objective. Later, we implemented a model that combines CNN and LSTM. 

In the next chapter, we will come to understand generative models. We will learn and implement style algorithms from scratch and cover a few of the best models. We will also cover the cool Generative Adversarial Networks (GAN) and its various applications.