Meet Drag Your GAN: An Interactive Point-based Manipulation on the Generative Image Manifold

Deep generative models, including generative adversarial networks (GANs), have produced random photorealistic pictures with unparalleled success. Controllability over the composite visual material is crucial for learning-based picture synthesis approaches in real-world applications. For instance, social media users may want to change the location, shape, expression, and body pose of a person or animal in a […]

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