Datasets › ImageNet-D
ImageNet-D
ImageNet-D contains 4835 test images featuring diverse backgrounds (3,764), textures (498), and materials (573). Generated by diffusion models, ImageNet-D achieves superior image fidelity and collection efficiency than prior studies. Evaluation results show that ImageNet-D results in a significant accuracy drop to a range of vision models, from the standard ResNet visual classifier to the latest foundation models like CLIP and MiniGPT-4, significantly reducing their accuracy by up to 60%.
Benchmarks archive 2025-07-28
No leaderboard in the archive resolves to this dataset.
Papers archive 2025-07-28
No paper in the archive has a leaderboard row on this dataset; the archive counts 4 papers for it but never published that list.
Dataset loaders archive 2025-07-28
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Tasks archive 2025-07-28
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License archive 2025-07-28
No licence recorded in the archive. Absence here is not a statement about the dataset's terms.
Modalities archive 2025-07-28
No modality tagged.
Languages archive 2025-07-28
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Variants archive 2025-07-28
- ImageNet-D
1 variant name, as the archive lists them.
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