What is DragGAN AI? Is the new tool better than Photoshop?

DragGAN AI is a new tool that allows users to edit images interactively using drag-and-drop controls that can change the way users edit images. Here is what you need to know about the new AI!

What is DragGAN AI? 

A group of researchers at the Max Planck Institute of Informatics and MIT CSAIL have deviced a new photo editing tool known as DragGAN where users can reshape and edit images interactively using AI technology. 

DragGAN is derived from “Drag-based Generative Adversarial Network” (GAN) that can generate images according to user needs, unlike other editing tools such as Photoshop that only distort or crop existing pixels.

R.I.P. Photoshop.

In just a few clicks, you'll be able to edit any image EXACTLY the way you want. 🤯pic.twitter.com/Nck3i50Mwb

— Lorenzo Green 〰️ (@mrgreen) May 19, 2023

The research paper mentions “Through DragGAN, anyone can deform an image with precise control over where pixels go, thus manipulating the pose, shape, expression, and layout of diverse categories such as animals, cars, humans, landscapes, etc. 

“As these manipulations are performed on the learned generative image manifold of a GAN, they tend to produce realistic outputs even for challenging scenarios such as hallucinating occluded content and deforming shapes that consistently follow the object's rigidity.” 

How to use DragGAN AI? 

DragGAN is still a white paper which means the users can’t test it. It is basically research that hasn’t been made public yet and users don’t get any app or website to use its features. 

Users can utilize DragGAN AI by following these steps: 

• Visit the DragGAN website (It is still under development)
• Click the “Upload Image” button and select your preferred image
• Click a point on the image and drag it to the desired spot
• When you release the point the image will move in the desired position. 
• Continue to adjust the image as required. 
• When you complete the editing, click the “Save” button to save the updated image. 

Source: Max Planck Institute of Informatics 

The research paper states “Our approach DragGAN allows users to "drag" the content of any GAN-generated images. Users only need to click a few handle points (red) and target points (blue) on the image, and our approach will move the handle points to precisely reach their corresponding target points. 

“Users can optionally draw a mask of the flexible region (brighter area), keeping the rest of the image fixed. This flexible point-based manipulation enables control of many spatial attributes like pose, shape, expression, and layout across diverse object categories.” 

What are the Features of DragGAN AI? 

Here are some of the features of DragGAN AI: 

• Point-based editing- The AI platform allows users to edit images directly on the screen by dragging and dropping points. This allows for more accurate and realistic adjustments than traditional image editing software.
• DragGAN allows users a 3D model integration- DragGAN takes it a step further by generating a 3D model of the image. This allows users to change the pose, shape, expression, and layout of objects in an image while keeping it logical and realistic.
• User-friendly interface- DragGAN promises to provide a straightforward and user-friendly experience for both experienced editors and beginners to AI image editing tools. The interface is designed to simplify the editing process and allow users to easily achieve the results they want.
• Potential for revolutionizing image editing- DragGAN has the potential to change the way we approach image editing due to its unique features. By combining point-based editing and 3D modeling, DragGAN pushes the boundaries of what is possible, giving users new avenues for artistic expression.

The research paper mentions “We conduct an extensive evaluation of DragGAN on diverse datasets including animals (lions, dogs, cats, and horses), humans (face and whole body), cars, and landscapes. 

“Our approach effectively moves the user-defined handle points to the target points, achieving diverse manipulation effects across many object categories. 

“Unlike conventional shape deformation approaches that simply apply warping [Igarashi et al. 2005], our deformation is performed on the learned image manifold of a GAN, which tends to obey the underlying object structures. 

“For example, our approach can hallucinate occluded content, like the teeth inside

a lion’s mouth, and can deform following the object’s rigidity, like the bending of a horse leg. We also develop a GUI for users to interactively perform the manipulation by simply clicking on the image.”