Tag: Vision Transformers: Rethinking

Vision Transformers (ViTs) have revolutionized the field of computer vision, offering a fresh perspective on how images are processed and understood by machines. Unlike traditional Convolutional Neural Networks (CNNs) that rely on local receptive fields and hierarchical feature extraction, ViTs leverage the transformer architecture, originally designed for natural language processing, to analyze images as sequences of patches. This novel approach has led to state-of-the-art performance on various image recognition tasks, opening new avenues for Innovation in areas such as object detection, image segmentation, and image generation. What are Vision Transformers? The Core Idea Behind ViTs Vision Transformers (ViTs) treat images as sequences of patches, much like how sentences are treated as s...