752 citations · 1.5k across the 33 of their papers we have counts for
4 papers · 1 filter
Blended Diffusion for Text-driven Editing of Natural Images
Omri Avrahami, Dani Lischinski, Ohad Fried
Natural language offers a highly intuitive interface for image editing. In this paper, we introduce the first solution for performing local (region-based) edits in generic natural…
StyleAlign: Analysis and Applications of Aligned StyleGAN Models
Zongze Wu, Yotam Nitzan, Eli Shechtman +1
In this paper, we perform an in-depth study of the properties and applications of aligned generative models. We refer to two models as aligned if they share the same architecture,…
GAN Cocktail: mixing GANs without dataset access
Omri Avrahami, Dani Lischinski, Ohad Fried
Today's generative models are capable of synthesizing high-fidelity images, but each model specializes on a specific target domain. This raises the need for model merging: combinin…
StyleCLIP: Text-Driven Manipulation of StyleGAN Imagery
Or Patashnik, Zongze Wu, Eli Shechtman +2
Inspired by the ability of StyleGAN to generate highly realistic images in a variety of domains, much recent work has focused on understanding how to use the latent spaces of Style…