Datasets › ImageNet-Atr
ImageNet-Atr (ImageNet with Adversarial Text Regions)
We build a new evaluation set by adding spotting words to the images of ImageNet 2012 evaluation sets. There are 1,000 categories in ImageNet. For each category c, we find its most confusing category c*and spot the category name to every evaluation image.
This evaluation set is challenging for many CLIP models. For example, OpenAI CLIP B-16 got a top-1 accuracy of as low as 32%, which is much lower than the original ImageNet evaluation set.
Benchmarks archive 2025-07-28
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Papers archive 2025-07-28
No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper 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
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Modalities archive 2025-07-28
Languages archive 2025-07-28
Variants archive 2025-07-28
- ImageNet-Atr
1 variant name, as the archive lists them.
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