1 code implementation • 19 Jul 2023 • Michal Geyer, Omer Bar-Tal, Shai Bagon, Tali Dekel
In this work, we present a framework that harnesses the power of a text-to-image diffusion model for the task of text-driven video editing.
no code implementations • CVPR 2023 • Dolev Ofri-Amar, Michal Geyer, Yoni Kasten, Tali Dekel
We present Neural Congealing -- a zero-shot self-supervised framework for detecting and jointly aligning semantically-common content across a given set of images.
3 code implementations • CVPR 2023 • Narek Tumanyan, Michal Geyer, Shai Bagon, Tali Dekel
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 complex visual concepts.
Ranked #10 on Text-based Image Editing on PIE-Bench
1 code implementation • 31 Oct 2021 • Nur Lan, Michal Geyer, Emmanuel Chemla, Roni Katzir
We train neural networks to optimize a Minimum Description Length score, i. e., to balance between the complexity of the network and its accuracy at a task.