DragGAN - Next-Level Image Editing Like You've Never Seen Before! Quick Demo
Channel: Curtis Pyke
Date: 2023-05-19

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Download DragGan paper here:  https://vcai.mpi-inf.mpg.de/projects/DragGAN/

A collaborative effort from researchers at Google, the Max Planck Institute of Informatics, and MIT CSAIL have unveiled DragGAN, a new approach to point-based image editing that uses pre-trained Generative Adversarial Networks (GANs). The technique precisely follows user input while maintaining the integrity of realistic images, without relying on domain-specific modeling or auxiliary networks. DragGAN optimizes latent codes, adjusting multiple handle points towards their target locations and tracking point trajectories, thus offering pixel-precise image deformations and interactive performance. This method is claimed to outperform current state-of-the-art GAN-based manipulation methods and signals a step forward in image editing using generative priors. The researchers aim to extend this technique to 3D generative models in the future.

In contrast to diffusion models used in tools like DALLE.2, Stable Diffusion, and Midjourney, GANs are proving to have a broader impact in this space. GANs use a dual-neural network setup - a generator and a discriminator - to create new, synthesized data instances. They became popular in 2017, three years after their proposal by Ian Goodfellow, whereas diffusion models, although offering stability and quality, have been gaining popularity more recently.

#draggan #GAN #drag gan