**ASLFeat** is a convolutional neural network for learning local features that uses deformable convolutional networks to densely estimate and apply local transformation. It also takes advantage of the inherent feature hierarchy to restore spatial resolution and low-level details for accurate keypoint localization. Finally, it uses a peakiness measurement to relate feature responses and derive more indicative detection scores.

**AdvProp** is an adversarial training scheme which treats adversarial examples as additional examples, to prevent overfitting. Key to the method is the usage of a separate auxiliary batch norm for adversarial examples, as they have different underlying distributions to normal examples.

AdvProp

Adversarial Examples Improve Image Recognition

ASLFeat

ASLFeat: Learning Local Features of Accurate Shape and Localization

**Random Grayscale**  is an image data augmentation that converts an image to grayscale with probability $p$.

Source	ASLFeat: Learning Local Features of Accurate Shape and Localization
Year	2000
Data Source	CC BY-SA - https://paperswithcode.com