Tamar Rott Shaham

I am a PhD candidate, supervised by Prof. Tomer Michaeli at the Electrical Engineering faculty of the Technion, where I also received my BSc.

My research interests include computer vision, machine learning and image processing.

Office: Mayer 514

Email / Google Scholar / Twitter / Github

News

[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

Publications

	Spatially-Adaptive Pixelwise Networks for Fast Image Translation Tamar Rott Shaham, Michaël Gharbi, Richard Zhang, Eli Shechtman, Tomer Michaeli arXiv, 2020 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 paper

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