I'm a Research Scientist at
Snap Research, leading the Personalized Generative AI effort.
My passion is synthesizing novel visual effects that are impactful and meaningful to people’s day to day.
I conduct research for various computer graphics applications using the power of Generative AI, and develop the next generation of cool, creative, generative features for Snap.
Prior to Snap I was a Research Scientist at
Google Research. I received my Ph.D from Tel-Aviv University where I was advised by
Daniel Cohen-Or.
I grew up in a small town in Israel called Zefat, lived in Tel-Aviv as an adult, spent 3 wonderful years in China as a researcher, and currently I’m based in the Bay Area (California).
I love to host at Snap (Palo Alto) students that are passionate about synthesis and visual effects, and I can host through the entire year!
If you would like to work with me, please reach out.
Email: kfiraberman@gmail.com /
Scholar /
Twitter
Orthogonal Adaptation for Modular Customization of Diffusion Models
Ryan Po, Guandao Yang,
Kfir Aberman, Gordon Wetzstein
CVPR 2024
Paper
Project
3D Paintbrush: Local Stylization of 3D Shapes with Cascaded Score Distillation
Dale Decatur, Itai Lang,
Kfir Aberman, Rana Hanocka
CVPR 2024
Paper
Project
HyperDreamBooth: HyperNetworks for Fast Personalization of Text-to-Image Models
Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Wei Wei, Tingbo Hou, Yael Pritch, Neal Wadhwa, Michael Rubinstein,
Kfir Aberman
CVPR 2024
Paper
Project
Realfill: Reference-Driven Generation for Authentic Image Completion
Luming Tang, Nataniel Ruiz, Qinghao Chu, Yuanzhen Li, Aleksander Holynski, David E Jacobs, Bharath Hariharan, Yael Pritch, Neal Wadhwa,
Kfir Aberman, Michael Rubinstein
Arxiv, 2023
Paper
Project
State of the Art on Diffusion Models for Visual Computing
Ryan Po, Wang Yifan, Vladislav Golyanik,
Kfir Aberman, Jonathan T Barron, Amit H Bermano, Eric Ryan Chan, Tali Dekel, Aleksander Holynski, Angjoo Kanazawa, C Karen Liu, Lingjie Liu, Ben Mildenhall, Matthias Nießner, Björn Ommer, Christian Theobalt, Peter Wonka, Gordon Wetzstein
Arxiv, 2023
Paper
Break-A-Scene: Extracting Multiple Concepts from a Single Image
Omri Avrahami,
Kfir Aberman, Ohad Fried, Daniel Cohen-Or, Dani Lischinski
SIGGRAPH Asia 2023
Paper
Project
Code (coming soon)
Delta Denoising Score
Amir Hertz,
Kfir Aberman, Daniel Cohen-Or
ICCV 2023
Paper
Project
Code (coming soon)
P+: Extended Textual Conditioning in Text-to-Image Generation
Andrey Voynov, Qinghao Chu, Daniel Cohen-Or,
Kfir Aberman
ArXiv, 2023
Paper
Project
Code (coming soon)
DreamBooth3D
Amit Raj, Srinivas Kaza, Ben Poole, Michael Niemeyer, Nataniel Ruiz, Ben Mildenhall, Shiran Zada,
Kfir Aberman, Michael Rubinstein, Jonathan Barron, Yuanzhen Li, Varun Jampani
ICCV 2023
Paper
Project
Sketch-Guided Text-to-Image Diffusion Models
Andrey Voynov,
Kfir Aberman, Daniel Cohen-Or
SIGGRAPH 2023
Paper
Project
Code (coming soon)
Null-Text Inversion for Editing Real Images using Guided Diffusion Models
Ron Mokady*, Amir Hertz*,
Kfir Aberman, Yael Pritch, Daniel Cohen-Or
CVPR 2023
Paper
Project
Code
DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation
Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Yael Pritch, Michael Rubinstein,
Kfir Aberman
CVPR 2023 (Best Paper Candidate)
Paper
Project
Dataset
Prompt-to-Prompt Image Editing with Cross Attention Control
Amir Hertz, Ron Mokady, Jay Tenenbaum,
Kfir Aberman, Yael Pritch, Daniel Cohen-Or
ICLR 2023
Paper
Project
Code
MyStyle: A Personalized Generative Prior
Yotam Nitzan,
Kfir Aberman, Qiurui He, Orly Liba, Michal Yarom, Yossi Gandelsman, Inbar Mosseri, Yael Pritch, Daniel Cohen-or
SIGGRAPH Asia 2022 (journal track)
Paper
Project
Video
Code
GANimator: Neural Motion Synthesis from a Single Sequence
Peizhuo Li,
Kfir Aberman, Zihan Zhang, Rana Hanocka, Olga Sorkine-Hornung
SIGGRAPH 2022 (journal track)
Paper
Project
Video
Code
MoDi: Unconditional Motion Synthesis from Diverse Data
Sigal Raab, Inbal Leibovitch, Peizhuo Li,
Kfir Aberman, Olga Sorkine-Hornung, Daniel Cohen-Or
CVPR 2023
Paper
Project
Video
Code
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
Rhythm is a Dancer: Music-Driven Motion Synthesis with Global Structure
Andreas Aristidou, Anastasios Yiannakidis,
Kfir Aberman, Daniel Cohen-Or, Ariel Shamir, Yiorgos Chrysanthou
IEEE TVCG 2021
Paper
Video
Learning Skeletal Articulations with Neural Blend Shapes
Peizhuo Li,
Kfir Aberman, Rana Hanocka, Libin Liu, Olga Sorkine-Hornung, Baoquan Chen
SIGGRAPH 2021
Paper
Project
Video
Code
MotioNet: 3D Human Motion Reconstruction from Video with Skeleton Consistency
Mingyi Shi,
Kfir Aberman, Andreas Aristidou, Taku Komura, Dani Lischinski, Daniel Cohen-Or, Baoquan Chen
Transactions on Graphics (ToG) 2020
Paper
Project
Video
Code
Skeleton-Aware Networks for Deep Motion Retargeting
Kfir Aberman*, Peizhuo Li*, Dani Lischinski, Olga Sorkine-Hornung, Daniel Cohen-Or, Baoquan Chen
SIGGRAPH 2020
Paper
Project
Video
Code
Unpaired Motion Style Transfer from Video to Animation
Kfir Aberman*, Yijia Weng*, Dani Lischinski, Daniel Cohen-Or, Baoquan Chen
SIGGRAPH 2020
Paper
Project
Video
Code
Learning Character-Agnostic Motion for Motion Retargeting in 2D
Kfir Aberman, Rundi Wu, Dani Lischinski, Chen Baoquan, Daniel Cohen-Or
SIGGRAPH 2019
Paper
Project
Video
Code
Deep Video-Based Performance Cloning
Kfir Aberman, Mingyi Shi, Jing Liao, Dani Lischinski, Chen Baoquan, Daniel Cohen-Or
Eurographics 2019
Paper
Video
Neural Best-Buddies: Sparse Cross-Domain Correspondence
Kfir Aberman, Jing Liao, Mingyi Shi, Dani Lischinski, Chen Baoquan, Daniel Cohen-Or
SIGGRAPH 2018
Paper
Project
Video
Code
Dip Transform for 3D Shape Reconstruction
Kfir Aberman, Oren Katzir, Qiang Zhou, Zegang Luo, Andrei Sharf, Chen Greif, Chen Baoquan, Daniel Cohen-Or
SIGGRAPH 2017
Paper
Sub-Nyquist SAR via Fourier Domain Range-Doppler Processing
Kfir Aberman, Yonina C. Eldar
IEEE Transactions on Geoscience and Remote Sensing 2017
Paper