Using Deep Learning to Understand and Synthesize Motion
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output
src
Autoencoder.ipynb
BBall.ipynb
ControlCenter.ipynb
ImageNetAutoencoder.ipynb
ImageNetVAE.ipynb
LatentLSTM-MMNIST.ipynb
LatentLSTM.ipynb
LatentLSTMGAN-MMNIST.ipynb
NatureFramesVAE.ipynb
README.md
TGIF.ipynb
VAE-MMnist.ipynb
VAE-Test.ipynb
VAE.ipynb
VAEGAN.ipynb
VAEGAN_MMNIST.ipynb
frameworkpython
requirements.txt
start_ipython_osx.sh

README.md

DeepGIFs: Using Deep Learning to Understand and Synthesize Motion

Authors: Ali Malik, Michael Troute, Brahm Capoor

Bouncing Ball Dataset

Ground Truth:

Ball GIF 1 Ball GIF 2

Generated Frames:

Ball GIF 1 Ball GIF 2

Moving MNIST Dataset

Ground Truth:

Ball GIF 1 Ball GIF 2

Generated Frames:

Ball GIF 1 Ball GIF 2