MetaFormer is a general architecture abstracted from Transformers by not specifying the token mixer.

**RandomHorizontalFlip** is a type of image data augmentation which horizontally flips a given image with a given probability.

Image Credit: [Apache MXNet](https://mxnet.apache.org/versions/1.5.0/tutorials/gluon/data_augmentation.html)

Random Horizontal Flip

MetaFormer

MetaFormer Is Actually What You Need for Vision

**Height-driven Attention Network**, or **HANet**, is a general add-on module for improving semantic segmentation for urban-scene images. It emphasizes informative features or classes selectively according to the vertical position of a pixel. The pixel-wise class distributions are significantly different from each other among horizontally segmented sections in the urban-scene images. Likewise, urban-scene images have their own distinct characteristics, but most semantic segmentation networks do not reflect such unique attributes in the architecture. The proposed network architecture incorporates the capability exploiting the attributes to handle the urban scene dataset effectively.

Source	MetaFormer Is Actually What You Need for Vision
Year	2000
Data Source	Papers with Code archive (CC BY-SA)