AI Image Generator by Art Neurona vs Drag Your GAN

Neurona from Art Neurona turns text prompts into images and keeps photo editing in the same browser workflow on art-neurona.com. You describe what you want, generate visuals, then adjust brightness, contrast, saturation, and backgrounds without switching tools. The same account covers face swap in photos and video, AI upscaling, retouching, and body shape edits.

Most image generation models stop at the first render. Neurona bundles face swap photo and video, figure correction, and background replacement next to text-to-image generation inside one credit wallet. That makes it faster for social posts and ad variants, but it is not built for layer-based design work in Photoshop or Figma.

Marketers, content creators, e-commerce sellers, and artists use Neurona to draft campaign graphics, Pinterest covers, product banners, and stylized art from prompts. Weekly, monthly, and annual plans include commercial use rights, watermark-free HD to 4K output, and access to the linked iPhone app.

Drag Your GAN lets you reshape a generated image by dragging handle points to target spots on the canvas. Instead of training on labeled pose data or 3D priors, DragGAN moves pixels inside a pretrained GAN's image manifold so edits stay photorealistic even when occluded regions get hallucinated. The project page hosts the SIGGRAPH 2023 paper, demo clips, and links to open source code.

Most GAN editors rely on fixed training annotations or 3D meshes, which limits what you can deform. DragGAN pairs feature-based motion supervision with discriminative point tracking so handle points follow your cursor while staying on the object surface. That makes it useful for nudging animal poses, facial expressions, car angles, and landscape layouts without retraining the generator.

Researchers, graphics students, and computer vision engineers use it to prototype interactive image editing workflows. The Max Planck Institute page distributes the paper PDF and GitHub repo under a non-commercial Creative Commons license, with contact details for the lead author.