Vision about Vision - An explanation of Transformers and generalist models in computer vision

Visual understanding at different levels of granularity has been a central challenge in computer vision, ranging from image classification to pixel-level segmentation. Vision Transformers and Vision Foundation Models brought a new approach, allowing generalist models to solve multiple visual tasks in an integrated way. We will explore the latest advances in this area, including DINO, DINOv2, and Masked Autoencoders, which are redefining how computing systems process images in a variety of applications. Let's highlight how these innovative models are unifying different levels of visual tasks and shaping the future of computer vision.