9 citations · 16 across the 3 of their papers we have counts for
5 papers
State-of-the-Art in the Architecture, Methods and Applications of StyleGAN
Amit H. Bermano, Rinon Gal, Yuval Alaluf +5
Generative Adversarial Networks (GANs) have established themselves as a prevalent approach to image synthesis. Of these, StyleGAN offers a fascinating case study, owing to its rema…
LARGE: Latent-Based Regression through GAN Semantics
Yotam Nitzan, Rinon Gal, Ofir Brenner +1
We propose a novel method for solving regression tasks using few-shot or weak supervision. At the core of our method is the fundamental observation that GANs are incredibly success…
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,…
Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation
Elad Richardson, Yuval Alaluf, Or Patashnik +4
We present a generic image-to-image translation framework, pixel2style2pixel (pSp). Our pSp framework is based on a novel encoder network that directly generates a series of style…
Face Identity Disentanglement via Latent Space Mapping
Yotam Nitzan, Amit Bermano, Yangyan Li +1
Learning disentangled representations of data is a fundamental problem in artificial intelligence. Specifically, disentangled latent representations allow generative models to cont…