367 citations · 407 across the 13 of their papers we have counts for
6 papers · 1 filter
Null-text Inversion for Editing Real Images using Guided Diffusion Models
Ron Mokady, Amir Hertz, Kfir Aberman +2
Recent text-guided diffusion models provide powerful image generation capabilities. Currently, a massive effort is given to enable the modification of these images using text only…
Text-Only Training for Image Captioning using Noise-Injected CLIP
David Nukrai, Ron Mokady, Amir Globerson
We consider the task of image-captioning using only the CLIP model and additional text data at training time, and no additional captioned images. Our approach relies on the fact th…
Prompt-to-Prompt Image Editing with Cross Attention Control
Amir Hertz, Ron Mokady, Jay Tenenbaum +3
Recent large-scale text-driven synthesis models have attracted much attention thanks to their remarkable capabilities of generating highly diverse images that follow given text pro…
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…
Self-Distilled StyleGAN: Towards Generation from Internet Photos
Ron Mokady, Michal Yarom, Omer Tov +5
StyleGAN is known to produce high-fidelity images, while also offering unprecedented semantic editing. However, these fascinating abilities have been demonstrated only on a limited…
Stitch it in Time: GAN-Based Facial Editing of Real Videos
Rotem Tzaban, Ron Mokady, Rinon Gal +2
The ability of Generative Adversarial Networks to encode rich semantics within their latent space has been widely adopted for facial image editing. However, replicating their succe…