Need help on GenAI on Images

Hello people,

I have done some courses on Generative AI using LLM where I got to know many methods using Large language models.

Now my question is what are the methods in GenAI using Images.

If someone could help, that means a lot to me.

Hello @Aravind.S ,

Generative AI methods for images include:

  1. Variational Autoencoders (VAEs): Learn a low-dimensional representation of images and generate new images from the learned latent space.
  2. Generative Adversarial Networks (GANs): Generate realistic images using a generator and discriminator network trained in a competitive manner.
  3. Conditional GANs: Condition the generator on additional information for image generation, like class labels or textual descriptions.
  4. Style Transfer: Transfer artistic styles from one image to another by separating style and content features.
  5. Autoencoders: Encode and reconstruct input images, with the decoder part used for generating new images.
  6. PixelRNN and PixelCNN: Generate images pixel by pixel, modeling the conditional distribution of each pixel based on previous ones.
  7. DeepDream: Enhance images by amplifying certain patterns using neural network activations.
  8. Neural Style Transfer: Combine the content of one image with the style of another to create unique visuals.
  9. CycleGAN: Learn mappings between two image domains without paired data, enabling image style transfer.
  10. Super-Resolution: Generate high-resolution images from low-resolution inputs using deep learning models.

These methods have revolutionized image generation, manipulation, and transformation in the field of Generative AI.

Hope this helps

Thank you so much aryan
Much appreciate your help :slight_smile:

No problem glad to help .