Caltech-UCSD Birds-200-2011 (CUB-200-2011) is a fine-grained image classification dataset of 200 bird species containing 11,788 images. Each image is annotated with a class label, one bounding box, 15 part locations, and 312 binary attributes. The dataset provides standard train/test splits (train: 5,994 images, test: 5,794 images) and is widely used as a benchmark for fine-grained categorization and part localization. Note: images overlap with ImageNet (caution when using ImageNet-pretrained models).
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