Inbar Mosseri

I'm leading a research group at Google Research in Tel-Aviv, focusing on image and video creation and editing using generative models. At the heart of my work is a deep passion for the intersection of AI and visual arts, where I'm constantly pushing the boundaries to explore how these cutting-edge technologies can revolutionize both academic research and the development of new product capabilities.

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Research & Product Highlights


I'm interested in computer vision, deep learning, generative AI, and image processing. Most of my recent research work focuses on generative models for image and video. Representative papers are highlighted.

Lumiere: A Space-Time Diffusion Model for Video Generation
Omer Bartal, Hila Chefer, Omer Tov, Charles Herrmann, Roni Paiss,
Shiran Zada, Ariel Efrat, Junhwa Hur , Yuanzhen Li
Tomer Michaeli, Oliver Wang, Deqing Sun, Tali Dekel,
Inbar Mosseri
arxiv, 2024

The Hidden Language of Diffusion Models
Hila Chefer, Oran Lang, Mor Geva, Volodymyr Polosukhin,
Assaf Shocher, Michal Irani, Inbar Mosseri, Lior Wolf
ICLR, 2024
Paper / Project

Imagic: Text-Based Real Image Editing with Diffusion Models
Bahjat Kawar, Shiran Zada, Oran Lang, Omer Tov, Huiwen Chang,
Tali Dekel, Inbar Mosseri, Michal Irani
CVPR, 2023
Paper / Project

MyStyle: A Personalized Generative Prior
Yotam Nitzan, Kfir Aberman, Qiurui He, Michal Yarom,
Yossi Gandelsman, Inbar Mosseri, Yael Pritch Daniel Cohen-or
SIGGRAPH Asia, 2022
Paper / Project / Video

Self-Distilled StyleGAN: Towards Generation from Internet Photos
Ron Mokady, Michal Yarom, Omer Tov, Oran Lang, Daniel Cohen-or
Michal Irani, Inbar Mosseri
Paper / Project

Deep Saliency Prior for Reducing Visual Distraction
Kfir Aberman, Junfeng He, Yossi Gandelsman, Inbar Mosseri,
David E. Jacobs, Kai Kohlhoff, Yael Pritch Michael Rubinstein
CVPR, 2022
Paper / Project

Explaining in Style: Training a GAN to explain a classifier in StyleSpace
Oran Lang, Yossi Gandelsman, Michal Yarom, Yoav Wald, Gal Elidan,
Avinatan Hassidim, William T. Freeman, Phillip Isola, Amir Globerson,
Michal Irani, Inbar Mosseri
CVPR, 2021
Paper / Project / Blog Post

SpeedNet: Learning the Speediness in Videos
Sagie Benaim, Ariel Efrat, Oran Lang, Inbar Mosseri, William T. Freeman,
Michael Rubinstein, Michal Irani, Tali Dekel
CVPR, 2020
Paper / Project

Semantic Pyramid for Image Generation
Assaf Shocher, Yossi Gandelsman, Inbar Mosseri, Michal Yarom, Michal Irani,
William T. Freeman, Tali Dekel
CVPR, 2020
Paper / Project

Speech2face: Learning the face behind a voice
Tae-Hyun Oh, Tali Dekel, Changil Kim, Inbar Mosseri, William T. Freeman,
Michael Rubinstein, Wojciech Matusik,
CVPR, 2019
Paper / Project

Looking to Listen at the Cocktail Party: A Speaker-Independent Audio-Visual Model for Speech Separation
Ariel Efrat, Inbar Mosseri, Oran Lang, Tali Dekel, Kevin Wilson, Avinatan Hassidim,
William T. Freeman, Michael Rubinstein
Paper / Project

Xgan: Unsupervised image-to-image translation for many-to-many mappings
Amelie Royer, Konstantinos Bousmalis, Stephan Gouws, Fred Bertsch,
Inbar Mosseri, Forrester Cole, Kevin Murphy
ICLR, 2018

Synthesizing normalized faces from facial identity features
Forrester Cole, David Belanger, Dilip Krishnan, Aaron Sarna Inbar Mosseri,
William T. Freeman,
CVPR, 2017

Combining the Power of Internal and External Denoising
Inbar Mosseri, Maria Zontak, Michal Irani
ICCP, 2013

Separating signal from noise using patch recurrence across scales
Maria Zontak, Inbar Mosseri, Michal Irani
CVPR, 2013
Paper / Project

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