Tamar Rott Shaham

I am a postdoctoral fellow with Antonio Torralba at CSAIL, MIT. During my PhD I worked with Tomer Michaeli at the Electrical & Computer Engineering faculty of the Technion, where I also received my BSc.

My research interests include computer vision, machine learning and human visual perception.

Office:      32-385

Email  /  Google Scholar  /  Twitter  /  Github

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[Oct 2021] Our paper GANs Spatial Control via Inference-Time Adaptive Normalization was accepted to WACV

[Sep 2021] Our works on single audio generative model and deep self-dissimilarities were accepted to NeurIPS

[Jun 2021] Check out our new paper about learning a generative model from a single short audio source

[Mar 2021] Our ASAPNet paper was accepted to CVPR

[Oct 2020] I participated in the IMVC2020's GANs panel

[Aug 2020] We are organizing the Deep Internal Learning (DIL) workshop in conjunction with ECCV 2020 (check out my joint keynote with Tomer)

[Jan 2020] I received the Adobe Research Fellowship

[Jan 2020] I gave a talk about SinGAN at the Israeli Computer Vision day

[Nov 2019] SinGAN won ICCV’19 Best Paper Award (Marr Prize)!

[Aug 2019] I participated in the Google Student Retreat at London, for Women Techmakers Scholars (now called Generation Google Scholarship), and met an amazing group of women from all over Europe, the Middle East and Africa

[July 2019] I am interning at Adobe Research Seattle for summer 2019, working with Eli Shechtman, Michaël Gharbi, and Richard Zhang

GANs Spatial Control via Inference-Time Adaptive Normalization
Karin Jakoel*, Liron Efraim*, Tamar Rott Shaham
WACV, 2022
paper / video / supplementals
Catch-A-Waveform: Learning to Generate Audio from a Single Short Example
Gal Greshler, Tamar Rott Shaham, Tomer Michaeli
NeurIPS, 2021
paper / web / code / supplementals
Deep Self-Dissimilarities as Powerful Visual Fingerprints
Idan Kligvasser, Tamar Rott Shaham, Yuval Bahat, Tomer Michaeli
NeurIPS, 2021
Spotlight presentation
paper / supplementals
Spatially-Adaptive Pixelwise Networks for Fast Image Translation
Tamar Rott Shaham, Michaël Gharbi, Richard Zhang, Eli Shechtman, Tomer Michaeli
CVPR, 2021
project page / arXiv
SinGAN: Learning a generative model from a single natural image
Tamar Rott Shaham, Tali Dekel, Tomer Michaeli
ICCV, 2019 
Best Paper Award (Marr Prize)
project page / arXiv / CVF / supp / code / ICCV talk / Israel Vision Day talk (recommended)
Deformation Aware image Compression
Tamar Rott Shaham, Tomer Michaeli
CVPR, 2018 
Spotlight presentation
project page / paper / code / spotlight
xUnit: Learning a Spatial Activation Function for Efficient Image Restoration
Idan Kligvasser Tamar Rott Shaham, Tomer Michaeli
CVPR, 2018 
Spotlight presentation
paper / code / spotlight (by Idan)

Visualizing Image Priors
Tamar Rott Shaham, Tomer Michaeli
ECCV, 2016 
project page / paper / poster
Edge Preserving Multi-Modal Registration Based On Gradient Intensity Self-Similarity
Tamar Rott Shaham, Dorin Shriki, Tamir Bendory
IEEEI, 2014 

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