The Describable Textures Dataset (DTD) is a benchmark dataset of textures “in the wild” designed for human-centric texture description and classification. It contains 5,640 images organized into 47 describable texture categories (120 images per category). Images are natural/web images and are annotated with a vocabulary of 47 texture attributes (semantic terms). The dataset provides predefined evaluation splits (DTD R1.0.1 uses a 1/3 train, 1/3 validation, 1/3 test split and the authors provide split files). DTD was introduced in the paper “Describing Textures in the Wild” (Cimpoi et al., CVPR 2014 / arXiv:1311.3618) and is widely used for texture classification and attribute-recognition tasks.
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