Tag: Vision Transformers: Attention

Imagine a world where Computers see images not as pixels, but as a sequence of words, much like we process sentences. This paradigm shift is happening thanks to Vision Transformers (ViTs), a revolutionary approach in computer vision that's borrowing heavily from the natural language processing (NLP) playbook. Forget the complex convolutions of traditional convolutional neural networks (CNNs); ViTs are opening up new possibilities for image recognition, object detection, and more, proving that sometimes, the best way to see is to "speak" in a new language. What are Vision Transformers? The Core Idea Vision Transformers, at their heart, are about applying the transformer architecture, which has achieved remarkable success in NLP, to the realm of image analysis. Instead of processing images t...

Vision Transformers (ViTs) are revolutionizing the field of computer vision, offering a powerful alternative to convolutional neural networks (CNNs). By adapting the transformer architecture, initially designed for natural language processing (NLP), ViTs achieve state-of-the-art performance on various image recognition tasks. This blog post delves into the inner workings of Vision Transformers, exploring their architecture, advantages, applications, and future directions. Understanding Vision Transformers: A Paradigm Shift in Image Recognition From CNNs to Transformers: The Evolution For years, CNNs have been the dominant architecture in computer vision. However, they have limitations in capturing long-range dependencies within images. Transformers, on the other hand, excel at this, making...