NUUR-Texture2953: A Diverse Dataset of High Resolution Homogeneous Textures

Permission to copy and use this dataset for noncommercial use is hereby granted provided this notice is retained in all copies and the dataset distribution and the paper mentioned below are clearly cited.

Contacts:
Jue Lin: jue.lin@u.northwestern.edu
Zhiwei Xu: zhiweixu2050@u.northwestern.edu
Gaurav Sharma: gaurav.sharma@rochester.edu
Thrasyvoulos N. Pappas: pappas@ece.northwestern.edu

"NUUR-Texture2953" is a dataset of diverse texture images created to facilitate research on texture analysis and synthesis, and is build upon our previously established dataset "NUUR-Texture500". The textures in this dataset are spatially homogeneous, ranging from regular to stochastic, typically containing repeated elements with random variations in position, shape, orientation and color. For a detailed description of the dataset construction and contents, readers should refer to the following paper:

Jue Lin, Zhiwei Xu, Gaurav Sharma, Thrasyvoulos N. Pappas, "Texture Representation via Analysis and Synthesis with Generative Adversarial Networks", Journal of e-Prime - Advances in Electrical Engineering, Electronics and Energy (2023), https://doi.org/10.1016/j.prime.2023.100286.

Jue Lin, Gaurav Sharma, Thrasyvoulos N. Pappas, "NUUR-Texture500: A Diverse Dataset of High Resolution Homogeneous Textures", Zenodo, https://doi.org/10.5281/zenodo.7127079

Disclaimer: 

The dataset is provided "as is" with ABSOLUTELY NO WARRANTY expressed or implied. Use at your own risk.

Acknowledgment: 

The NUUR-Texture2953 texture images are curated from a number of publicly accessible sources. We acknowledge and thank the original sites for their contributions:
Flickr www.flickr.com
NeedPix www.needpix.com
Pexels www.pexels.com
PickUpImage www.pickupimage.com
Pixabay www.pixabay.com
PublicDomainPictures www.publicdomainpictures.net
RawPixel www.rawpixel.com
Unsplash www.unsplash.com
WikimediaCommons commons.wikimedia.org