This repository contains three Google Colab notebooks, each of which is a part of assignment-3 of CS231n: Convolutional Neural Networks for Visual Recognition course by Stanford, Spring 2020.
I have inclued three questions from the assignment-3, which also serves as applications of Computer Vision algorithms.
- Network Visualization (Saliency maps, Class Visualization, and Fooling Images)
- Neural Style Transfer
- Generative Adversarial Networks (GANs)
All the three problems are implemented using the PyTorch framework. If you are new to PyTorch, you can have a look at this repository as a starting point.
I have also attempted the inline questions asked in the notebooks. Feel free to suggest any modifications or suggestions. Also, please let me know if there are any errors/mistakes in my implementations.
You can view the CS231n course notes here. Also the lecture series of the CS231n can be found below:
- Spring, 2017 by Justin Johnson, Serena Yeung and Fei-Fei Li
- Winter, 2016 by Andrej Karpathy, Fei-Fei Li, Justin Johnson
I would also like to thank all the people who are responsible for creating this wonderful course and publishing it online.