ImageNet-9 consists of images with different amounts of background and foreground signal, which you can use to measure the extent to which your models rely on image backgrounds. This dataset is helpful in testing the robustness of vision models with respect to their dependence on the backgrounds of images.
Variants: ImageNet-9
This dataset is used in 1 benchmark:
| Task | Model | Paper | Date |
|---|---|---|---|
| Image Classification | SqueezeNet + Simple Bypass | SqueezeNet: AlexNet-level accuracy with 50x … | 2016-02-24 |
Recent papers with results on this dataset: