In this post, we will review and summarize the Swin Transformer paper, titled as  Swin Transformer: Hierarchical Vision Transformer using Shifted Windows . Some of the code used here will be obtained from this Github Repo , so you better clone it in case you want to test some of this work, However, the aim of this post is to better simplify and summarize the Swin transformer paper. Soon, there will be another Post explaining how to implement the Swin Transformer in details.  Overview The "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" is a research paper that proposes a new architecture for visual recognition tasks using a hierarchical transformer model. The architecture, called the Swin Transformer, uses a combination of local and global attention mechanisms to process images and improve the accuracy of image classification and object detection tasks. The Swin Transformer uses a series of shifted window attention mechanisms to enable the model to