Moab Arar

I am a Research Scientist at FAIR (Meta)

My research focuses on Generative Video Models, Real-time Video Generation, and World Models.

I completed my PhD at Tel Aviv University, advised by Amit Bermano and Ariel Shamir. Previously, I was a research intern at Google and Meta.

Publications

Diffusion Models Are Real-Time Game Engines Dani Valevski* , Yaniv Leviathan* , Moab Arar*, Shlomi Fruchter* Accepted to ICLR, 2025. Paper Page
PALP: Prompt Aligned Personalization of Text-to-Image Models Moab Arar, Andrey Voynov, Amir Hertz, Omri Avrahami, Shlomi Fruchter, Yael Pritch, Daniel Cohen-Or, Ariel Shamir SIGGRAPH Asia, 2024. Paper Page
Curved Diffusion: A Generative Model With Optical Geometry Control Andrey Voynov, Amir Hertz, Moab Arar, Shlomi Fruchter, Daniel Cohen-Or, ECCV, 2024. Paper Page
The Chosen One: Consistent Characters in Text-to-Image Diffusion Models Omri Avrahami, Amir Hertz, Yael Vinker, Moab Arar, Shlomi Fruchter, Ohad Fried, Daniel Cohen-Or, Dani Lischinski, SIGGRAPH, 2024. Paper Page
Single Motion Diffusion Sigal Rab*, Inbal Leibovitch*, Guy Tevet, Moab Arar, Amit H Bermano, Daniel Cohen-Or ICLR 2024 (spotlight - top 5%). Paper Page Code
Domain-Agnostic Tuning-Encoder for Fast Personalization of Text-To-Image Models Moab Arar, Rinon Gal, Yuval Atzmon, Gal Chechik, Daniel Cohen-Or, Ariel Shamir, Amit H Bermano SIGGRAPH Asia, 2023. Paper Page
Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Models Rinon Gal, Moab Arar, Yuval Atzmon, Amit H Bermano, Gal Chechik, Daniel Cohen-Or SIGGRAPH, 2023. Paper Page
Learned Queries for Efficient Local Attention Moab Arar , Ariel Shamir , Amit H Bermano CVPR, 2022 (Oral). Paper Code
InAugment: Improving Classifiers via Internal Augmentation Moab Arar , Ariel Shamir , Amit H Bermano ICCV Workshops, 2021. Paper
Unsupervised Multi-Modal Image Registration via Geometry Preserving Image-to-Image Translation Moab Arar , Yiftach Ginger , Dov Danon , Ilya Leizerson, Amit H Bermano , Daniel Cohen-Or CVPR, 2020. Paper Code

Talks

Sep, 2024	ML Seminar @ CMU: Deep Neural Components and Training Methodologies in Vision
May, 2022	ML Seminar @ Google, New-York: Learned Queries for Efficient Local Attention
May, 2022	ML Seminar @ Amazon, Tel-Aviv: Learned Queries for Efficient Local Attention

Publications

Talks

Contact Me