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Downsampled Imagenet
No Label
Common
|...
License: Unknown

Overview

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.

Data Summary
Type
Image,
Amount
--
Size
15.71GB
Provided by
Stanford Vision Lab
The Stanford Vision and Learning Lab (SVL) at Stanford is directed by Professors Fei-Fei Li, Juan Carlos Niebles, Silvio Savarese and Jiajun Wu. We are tackling fundamental open problems in computer vision research and are intrigued by visual functionalities that give rise to semantically meaningful interpretations of the visual world.
| Amount -- | Size 15.71GB
Downsampled Imagenet
No Label
Common
License: Unknown

Overview

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.

0
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