Vision Transformers: Seeing Beyond Convolutional Boundaries.
Vision Transformers (ViTs) have revolutionized the field of computer vision, offering a fresh perspective on image recognition and processing. Departing from the traditional reliance on convolutional neural networks (CNNs), ViTs leverage the transformer architecture, which has achieved remarkable success in natural language processing (NLP), to analyze images as sequences of patches. This innovative approach has unlocked new possibilities in various vision-related tasks, achieving state-of-the-art results and paving the way for future advancements.
What are Vision Transformers?
The Core Idea
Vision Transformers apply the transformer architecture, originally designed for NLP, to image recognition tasks. Instead of processing images as a grid of pixels (like CNNs), ViTs split an image into s...








