472 citations · 624 across the 37 of their papers we have counts for
6 papers · 1 filter
StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators
Rinon Gal, Or Patashnik, Haggai Maron +2
Can a generative model be trained to produce images from a specific domain, guided by a text prompt only, without seeing any image? In other words: can an image generator be traine…
StyleFusion: A Generative Model for Disentangling Spatial Segments
Omer Kafri, Or Patashnik, Yuval Alaluf +1
We present StyleFusion, a new mapping architecture for StyleGAN, which takes as input a number of latent codes and fuses them into a single style code. Inserting the resulting styl…
ReStyle: A Residual-Based StyleGAN Encoder via Iterative Refinement
Yuval Alaluf, Or Patashnik, Daniel Cohen-Or
Recently, the power of unconditional image synthesis has significantly advanced through the use of Generative Adversarial Networks (GANs). The task of inverting an image into its c…
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…
Designing an Encoder for StyleGAN Image Manipulation
Omer Tov, Yuval Alaluf, Yotam Nitzan +2
Recently, there has been a surge of diverse methods for performing image editing by employing pre-trained unconditional generators. Applying these methods on real images, however,…
Only a Matter of Style: Age Transformation Using a Style-Based Regression Model
Yuval Alaluf, Or Patashnik, Daniel Cohen-Or
The task of age transformation illustrates the change of an individual's appearance over time. Accurately modeling this complex transformation over an input facial image is extreme…