What is ViT?

ViT, or Vision Transformer, is a deep learning model that applies the Transformer architecture (originally designed for natural language processing) to computer vision tasks. Instead of processing images as pixels, ViT splits an image into patches and treats each patch as a token, similar to how words are treated in NLP. These patches are then linearly embedded and passed through a standard Transformer encoder. ViT models have achieved state-of-the-art results on image classification tasks and are commonly used for tasks like image recognition, object detection, and image segmentation.