The ability of AI tools to manipulate images continues to grow. The latest example is shown in a research paper from the Max Planck Institute. For now, it’s “only” a research paper, but a very impressive one, letting users drag elements of a picture to change their appearance. Not only can you change the dimensions of a car or manipulate a smile into a frown with a simple click and drag, but you can rotate a picture’s subject as if it were a 3D model — changing the direction someone is facing, for example. Another option is to adjust the reflections on a lake or the height of a mountain with a few clicks. Traditional methods for controlling Generative Adversarial Networks (GANs) rely on manually annotated data or prior 3D models. However, these approaches often lack precision, flexibility, and generality. In response to these shortcomings, Max Planck Institute introduces DragGAN, a novel approach that allows users to interactively “drag” any points in an image to target locations. DragGAN comprises two main components: a feature-based motion supervision and a new point-tracking approach. The motion supervision allows for user-guided movement of handle points in the image towards target positions. The point-tracking approach leverages distinctive generator features to keep track of the handle points’ locations as they are moved.
