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

**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.

ASLFeat

ASLFeat: Learning Local Features of Accurate Shape and Localization

Random Grayscale

[Transformer](https://paperswithcode.com/method/transformer)-Decoder is a modification to Transformer-Encoder-Decoder for long sequences that drops the encoder
module, combines the input and output sequences into a single ”sentence” and is trained as a standard language model. It is used in [GPT](https://paperswithcode.com/method/gpt) and later revisions.

Year	2000
Data Source	CC BY-SA - https://paperswithcode.com