📂 Art 👁 1.8k views 🕐 June 8, 2026

DragGAN

DragGAN is an official code for interactive point-based manipulation on the generative.

DragGAN is an official code for interactive point-based manipulation on the generative image manifold, presented at SIGGRAPH 2023. It is designed for researchers and developers who want to edit GAN-generated images with precision. The tool allows for real-time manipulation of images, enabling users to create complex and detailed edits. DragGAN is particularly useful for applications where image realism is crucial, such as in film, video games, and advertising. The code is built on top of StyleGAN3 and is available on GitHub, making it accessible to a wide range of users. By leveraging the power of generative models, DragGAN provides a unique solution for image editing, allowing users to create high-quality images with ease.

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Features
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Interactive Point-based Manipulation
allows for precise editing of GAN-generated images
⟐
Generative Image Manifold
enables real-time manipulation of images on the generative manifold
⬡
StyleGAN3 Integration
built on top of StyleGAN3, providing a robust foundation for image editing
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Gradio Visualizer
provides a user-friendly interface for editing images
Verdict
Best forTeams doing Art work who need consistent output without a steep learning curve.
Skip ifYou only need this once or twice; the subscription cost won't pay off for occasional use.
✓Enables precise editing of GAN-generated images, allowing for high-quality image creation
✓Built on top of StyleGAN3, providing a robust foundation for image editing
✓Includes pre-trained model weights, making it easy to get started with image editing
✕Requires technical expertise to use, particularly for those without experience in deep learning or computer vision
✕Docker image takes up significant disk space, requiring substantial storage resources
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Frequently Asked Questions
DragGAN is an official code for interactive point-based manipulation on the generative image manifold, presented at SIGGRAPH 2023. It allows for precise editing of GAN-generated images.
DragGAN works by enabling real-time manipulation of images on the generative manifold, using a combination of StyleGAN3 and interactive point-based manipulation.
The system requirements for DragGAN include a significant amount of disk space, as the Docker image takes up around 25GB, and a compatible operating system, such as Linux or MacOS.
The code related to the DragGAN algorithm is licensed under CC-BY-NC, which allows for non-commercial use, but most of the project is available under a separate license terms, including the Nvidia Source Code License.
DragGAN is unique in its ability to enable interactive point-based manipulation on the generative image manifold, making it particularly useful for applications where image realism is crucial, such as in film, video games, and advertising.
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