Audience

Users that want to manipulate images using AI

About DragGAN

Synthesizing visual content that meets users' needs often requires flexible and precise controllability of the pose, shape, expression, and layout of the generated objects. Existing approaches gain controllability of generative adversarial networks (GANs) via manually annotated training data or a prior 3D model, which often lack flexibility, precision, and generality. In this work, we study a powerful yet much less explored way of controlling GANs, that is, to "drag" any points of the image to precisely reach target points in a user-interactive manner, as shown in Fig.1. To achieve this, we propose DragGAN, which consists of two main components including: 1) a feature-based motion supervision that drives the handle point to move towards the target position, and 2) a new point tracking approach that leverages the discriminative GAN features to keep localizing the position of the handle points. Through DragGAN, anyone can deform an image with precise control over where pixels go.

Pricing

Starting Price:
Free
Pricing Details:
Open source
Free Version:
Free Version available.

Integrations

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Company Information

DragGAN
Founded: 2023
vcai.mpi-inf.mpg.de/projects/DragGAN/

Videos and Screen Captures

DragGAN Screenshot 1
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Product Details

Platforms Supported
Windows
Mac
Linux
Training
Documentation

DragGAN Frequently Asked Questions

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DragGAN Product Features