|
--- |
|
license: cc-by-nc-4.0 |
|
dataset_info: |
|
features: |
|
- name: image |
|
dtype: image |
|
- name: world_name |
|
dtype: string |
|
- name: character_name |
|
dtype: string |
|
- name: character_scale |
|
dtype: float64 |
|
- name: camera_yaw |
|
dtype: int64 |
|
- name: character_texture |
|
dtype: string |
|
splits: |
|
- name: train |
|
num_bytes: 82030062942.72 |
|
num_examples: 215040 |
|
download_size: 84628407574 |
|
dataset_size: 82030062942.72 |
|
configs: |
|
- config_name: default |
|
data_files: |
|
- split: train |
|
path: data/train-* |
|
--- |
|
|
|
## PUG Animals |
|
The PUG: Animals dataset contains 215,040 pre-rendered images based on Unreal-Engine using 70 animal assets, 64 environments, 3 sizes, 4 textures, under 4 camera orientations. |
|
It was designed with the intent to create a dataset with variation factors available. Inspired by research on out-of-distribution generalization, PUG: Animals allows one to precisely control distribution shifts between training and testing which can provide better insight on how a deep neural network generalizes on held out variation factors. |
|
|
|
## LICENSE |
|
The datasets are distributed under the CC-BY-NC, with the addenda that they should not be used to train Generative AI models. |
|
|
|
## Citing PUG |
|
If you use one of the PUG datasets, please cite: |
|
``` |
|
@misc{bordes2023pug, |
|
title={PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning}, |
|
author={Florian Bordes and Shashank Shekhar and Mark Ibrahim and Diane Bouchacourt and Pascal Vincent and Ari S. Morcos}, |
|
year={2023}, |
|
eprint={2308.03977}, |
|
archivePrefix={arXiv}, |
|
primaryClass={cs.CV} |
|
} |
|
``` |
|
|
|
## To learn more about the PUG datasets: |
|
Please visit the [website](https://pug.metademolab.com/) and the [github](https://github.com/facebookresearch/PUG) |
