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PyTorch implementation of Autoencoder for 360 images , the encoder leverage vgg convolutions weight

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mtliba/360-images-VGG-based-Autoencoder-Pytorch

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360-images-VGG-based-Autoencoder-Pytorch

  • PyTorch implementation of Autoencoder for 360 images , the encoder leverage vgg convolutions weight , in order to adapt 360 images characteristic last maxpooling layer has removed ,third and fourth maxpooling layer are set to 4 pooling factor instead of 2 in order to have a receptive field of (580,580) which cover the whole input (576,288)
    to run this project just specify your root_dir in main.py .

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PyTorch implementation of Autoencoder for 360 images , the encoder leverage vgg convolutions weight

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