* Paper: "ImageNet Large Scale Visual Recognition Challenge" - https://arxiv.org/abs/1409.0575
The standard 50,000 image ImageNet-1k validation set. Model selection during training utilizes this validation set, so it is not a true test set.
The standard 50,000 image ImageNet-1k validation set. Model selection during training utilizes this validation set, so it is not a true test set. Question: Does anyone have the official ImageNet-1k test set classification labels now that challenges are done?
### ImageNetV2 Matched Frequency - [`results-imagenetv2-matched-frequency.csv`](results-imagenetv2-matched-frequency.csv)
@ -32,7 +32,7 @@ An ImageNet test set of 10,000 images sampled from new images roughly 10 years a
A collection of 7500 images covering 200 of the 1000 ImageNet classes. Images are naturally occuring adversarial examples that confuse typical ImageNet classifiers. This is a challenging dataset, your average ResNet-50 will score 0% top-1.
A collection of 7500 images covering 200 of the 1000 ImageNet classes. Images are naturally occuring adversarial examples that confuse typical ImageNet classifiers. This is a challenging dataset, your typical ResNet-50 will score 0% top-1.
## TODO
* Add rank difference, and top-1/top-5 difference from ImageNet-1k validation for the 3 additional test sets