Vision Transformers: Attentions Leap Into Semantic Scene Understanding.
Vision Transformers are revolutionizing the field of computer vision, challenging the dominance of convolutional neural networks (CNNs) that have reigned supreme for years. By adapting the Transformer architecture, initially designed for natural language processing, to image data, Vision Transformers (ViTs) achieve state-of-the-art results on image classification and other vision tasks. This blog post will delve into the inner workings of ViTs, explore their advantages and limitations, and discuss their growing impact on the future of computer vision.
What are Vision Transformers (ViTs)?
Vision Transformers (ViTs) represent a paradigm shift in how we approach image processing. Instead of relying on convolutions to extract features, ViTs treat images as sequences of patches and leverage the...