Natural Adversarial Object
Natural Adversarial Objects (NAO) is a new dataset to evaluate the robustness of object detection models. NAO contains 7,934 images and 9,943 objects that are unmodified and representative of real-world scenarios, but cause state-of-the-art detection models to misclassify with high confidence.
Variants: NAO
This dataset is used in 1 benchmark:
Task | Model | Paper | Date |
---|---|---|---|
Object Detection | RetinaNet-R50 | Natural Adversarial Objects | 2021-11-07 |
Object Detection | YOLOv3 | Natural Adversarial Objects | 2021-11-07 |
Object Detection | EfficientDet-D2 | Natural Adversarial Objects | 2021-11-07 |
Object Detection | Mask RCNN R50 | Natural Adversarial Objects | 2021-11-07 |
Object Detection | EfficientDet-D4 | Natural Adversarial Objects | 2021-11-07 |
Object Detection | EfficientDet-D7 | Natural Adversarial Objects | 2021-11-07 |
Object Detection | Faster RCNN | Natural Adversarial Objects | 2021-11-07 |
Recent papers with results on this dataset: