geirhos_conflict_stimuli

• Description:

Shape/texture conflict stimuli from "ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness."

Note that, although the dataset source contains images with matching shape and texture and we include them here, they are ignored for most evaluations in the original paper.

• Homepage: https://github.com/rgeirhos/texture-vs-shape

• Source code: tfds.image_classification.GeirhosConflictStimuli

• Versions:

  • 1.0.0 (default): No release notes.

• Download size: 153.96 MiB

• Dataset size: 130.44 MiB

• Auto-cached (documentation): Only when shuffle_files=False (test)

• Splits:

Split	Examples
'test'	1,280

• Feature structure:

FeaturesDict({
    'file_name': Text(shape=(), dtype=string),
    'image': Image(shape=(None, None, 3), dtype=uint8),
    'shape_imagenet_labels': Sequence(ClassLabel(shape=(), dtype=int64, num_classes=1000)),
    'shape_label': ClassLabel(shape=(), dtype=int64, num_classes=16),
    'texture_imagenet_labels': Sequence(ClassLabel(shape=(), dtype=int64, num_classes=1000)),
    'texture_label': ClassLabel(shape=(), dtype=int64, num_classes=16),
})

• Feature documentation:

Feature	Class	Shape	Dtype	Description
	FeaturesDict
file_name	Text		string
image	Image	(None, None, 3)	uint8
shape_imagenet_labels	Sequence(ClassLabel)	(None,)	int64
shape_label	ClassLabel		int64
texture_imagenet_labels	Sequence(ClassLabel)	(None,)	int64
texture_label	ClassLabel		int64

• Supervised keys (See as_supervised doc): ('image', 'shape_label')

• Figure (tfds.show_examples):

• Examples (tfds.as_dataframe):

• Citation:

@inproceedings{
  geirhos2018imagenettrained,
  title={ImageNet-trained {CNN}s are biased towards texture; increasing shape
         bias improves accuracy and robustness.},
  author={Robert Geirhos and Patricia Rubisch and Claudio Michaelis and
          Matthias Bethge and Felix A. Wichmann and Wieland Brendel},
  booktitle={International Conference on Learning Representations},
  year={2019},
  url={https://openreview.net/forum?id=Bygh9j09KX},
}