587 citations · 902 across the 38 of their papers we have counts for
6 papers · 1 filter
Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translation
Narek Tumanyan, Michal Geyer, Shai Bagon +1
Large-scale text-to-image generative models have been a revolutionary breakthrough in the evolution of generative AI, allowing us to synthesize diverse images that convey highly co…
Imagic: Text-Based Real Image Editing with Diffusion Models
Bahjat Kawar, Shiran Zada, Oran Lang +5
Text-conditioned image editing has recently attracted considerable interest. However, most methods are currently either limited to specific editing types (e.g., object overlay, sty…
Text2LIVE: Text-Driven Layered Image and Video Editing
Omer Bar-Tal, Dolev Ofri-Amar, Rafail Fridman +2
We present a method for zero-shot, text-driven appearance manipulation in natural images and videos. Given an input image or video and a target text prompt, our goal is to edit the…
Diverse Video Generation from a Single Video
Niv Haim, Ben Feinstein, Niv Granot +4
GANs are able to perform generation and manipulation tasks, trained on a single video. However, these single video GANs require unreasonable amount of time to train on a single vid…
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…
Splicing ViT Features for Semantic Appearance Transfer
Narek Tumanyan, Omer Bar-Tal, Shai Bagon +1
We present a method for semantically transferring the visual appearance of one natural image to another. Specifically, our goal is to generate an image in which objects in a source…