​​Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold
Meet DragGAN, a groundbreaking approach that is set to revolutionize the way we control generative adversarial networks (GANs) and synthesize visual content! This innovative tool offers users unprecedented flexibility and precision when manipulating images, sidestepping the limitations of prior 3D models and annotated training data. With DragGAN, you can now "drag" any point of an image to a precise target position, introducing a nvel user-interactive element.
Two ingenious components underpin DragGAN's functionality: the first is a feature-based motion supervision that effortlessly guides the handle point towards the desired position, and the second is a novel point tracking approach that utilizes the discriminating features of the generator to maintain the handle points' positions. The real game-changer is that anyone can now deform an image with absolute control over pixel movements, enabling the manipulation of pose, shape, expression, and layout across diverse categories like animals, cars, humans, landscapes, and more. DragGAN outperforms its predecessors in both image manipulation and point tracking tasks, promising an exciting leap forward in AI-generated visual content!
Paper link: https://arxiv.org/abs/2305.10973
Code link: https://github.com/XingangPan/DragGAN
Project link: https://vcai.mpi-inf.mpg.de/projects/DragGAN/
A detailed unofficial overview of the paper: https://andlukyane.com/blog/paper-review-draggan
#deeplearning #cv #gan #imagemanipulation
Meet DragGAN, a groundbreaking approach that is set to revolutionize the way we control generative adversarial networks (GANs) and synthesize visual content! This innovative tool offers users unprecedented flexibility and precision when manipulating images, sidestepping the limitations of prior 3D models and annotated training data. With DragGAN, you can now "drag" any point of an image to a precise target position, introducing a nvel user-interactive element.
Two ingenious components underpin DragGAN's functionality: the first is a feature-based motion supervision that effortlessly guides the handle point towards the desired position, and the second is a novel point tracking approach that utilizes the discriminating features of the generator to maintain the handle points' positions. The real game-changer is that anyone can now deform an image with absolute control over pixel movements, enabling the manipulation of pose, shape, expression, and layout across diverse categories like animals, cars, humans, landscapes, and more. DragGAN outperforms its predecessors in both image manipulation and point tracking tasks, promising an exciting leap forward in AI-generated visual content!
Paper link: https://arxiv.org/abs/2305.10973
Code link: https://github.com/XingangPan/DragGAN
Project link: https://vcai.mpi-inf.mpg.de/projects/DragGAN/
A detailed unofficial overview of the paper: https://andlukyane.com/blog/paper-review-draggan
#deeplearning #cv #gan #imagemanipulation
