Abstract: This page includes downsampled ImageNet images, which can be used for density estimation and generative modeling experiments. Images come in two resolutions: 32x32 and 64x64, and were introduced in Pixel Recurrent Neural Networks. Please refer to the Pixel RNN paper for more details and results.

This page includes downsampled ImageNet images, which can be used for density estimation and generative modeling experiments. Images come in two resolutions: 32x32 and 64x64, and were introduced in Pixel Recurrent Neural Networks. Please refer to the Pixel RNN paper for more details and results.
URL: http://image-net.org/small/download.phpLicense: No license specified, the work may be protected by copyright.
@article{,
title= {Downsampled ImageNet 64x64},
keywords= {},
author= {Aaron van den Oord and Nal Kalchbrenner and Koray Kavukcuoglu},
abstract= {This page includes downsampled ImageNet images, which can be used for density estimation and generative modeling experiments. Images come in two resolutions: 32x32 and 64x64, and were introduced in Pixel Recurrent Neural Networks. Please refer to the Pixel RNN paper for more details and results.
},
terms= {},
license= {},
superseded= {},
url= {http://image-net.org/small/download.php}
}