GitHub - srinadhu/CS231n_assignment3: Implemented Vanilla RNN and LSTM networks, combined these with pretrained VGG-16 on ImageNet to build image captioning models on Microsoft COCO dataset. Explored use of image gradients for generating new images and techniques used are Saliency Maps, Fooling Images and Class Visualization. Implemented image Style Transfer technique from 'Image Style Transfer Using Convolutional Neural Networks'. Implemented and trained GAN, LS-GAN and DC-GAN on MNIST dataset to produce images that resemble samples from MNIST, DC-GAN gave best resembling images.

Branches Tags

Name		Name	Last commit message	Last commit date
Latest commit History 8 Commits
cs231n		cs231n
styles		styles
GANs-PyTorch.ipynb		GANs-PyTorch.ipynb
LSTM_Captioning.ipynb		LSTM_Captioning.ipynb
NetworkVisualization-PyTorch.ipynb		NetworkVisualization-PyTorch.ipynb
README.md		README.md
RNN_Captioning.ipynb		RNN_Captioning.ipynb
StyleTransfer-PyTorch.ipynb		StyleTransfer-PyTorch.ipynb
example_styletransfer.png		example_styletransfer.png
gan-checks-tf.npz		gan-checks-tf.npz
gan_outputs_pytorch.png		gan_outputs_pytorch.png
kitten.jpg		kitten.jpg
sky.jpg		sky.jpg
style-transfer-checks.npz		style-transfer-checks.npz

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Implemented Vanilla RNN and LSTM networks, combined these with pretrained VGG-16 on ImageNet to build image captioning models on Microsoft COCO dataset. Explored use of image gradients for generating new images and techniques used are Saliency Maps, Fooling Images and Class Visualization. Implemented image Style Transfer technique from 'Image St…

cs231n.github.io/assignments2018/assignment3/