Introduction

Deformable attention is a type of attention mechanism that allows neural networks to focus on different parts of an input image with varying levels of detail. This is achieved by learning a set of spatial transformations that can be applied to the input image before computing the attention weights. By allowing the network to deform the input image in this way, deformable attention can capture complex spatial relationships in the data and improve the performance of computer vision tasks such as object detection, image segmentation, and image classification.