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XIMAGENET-12

XIMAGENET-12 is an explainable visual benchmark dataset for model robustness evaluation. It consists of over 200K images with 15,410 manual semantic annotations. The dataset is designed to simulate real-world situations and evaluate the robustness of visual models.

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Cite this as

Qiang Li, Dan Zhang, Shengzhao Lei, Xun Zhao, Weiwei Li, Porawit Kamnoedboon, Junhao Dong, Shuyan Li (2024). Dataset: XIMAGENET-12. https://doi.org/10.57702/c5tgndcx

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Additional Info

Field Value
Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.2310.08182
Author Qiang Li
More Authors
Dan Zhang
Shengzhao Lei
Xun Zhao
Weiwei Li
Porawit Kamnoedboon
Junhao Dong
Shuyan Li
Homepage https://sites.google.com/view/ximagenet-12/home