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T. Michaeli

77 papers hereh-index 348k citations160 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author4
  • middle author27
  • last author44

Across the 75 of 77 papers where every author was matched, so the position is known.

fields
  • cs.CV36
  • eess.IV12
  • cs.LG11
  • cs.IT6
  • physics.optics4
  • stat.ML3
same name
  • T. Michaeli — 2 papers, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20082026
most citedThe Perception-Distortion Tradeoff

997 citations · 2.4k across the 65 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.CV2019

Explorable Super Resolution

Yuval Bahat, Tomer Michaeli

Single image super resolution (SR) has seen major performance leaps in recent years. However, existing methods do not allow exploring the infinitely many plausible reconstructions…

eess.IV2019★ 332 cited

DeepSTORM3D: dense three dimensional localization microscopy and point spread function design by deep learning

Elias Nehme, Daniel Freedman, Racheli Gordon +6

Localization microscopy is an imaging technique in which the positions of individual nanoscale point emitters (e.g. fluorescent molecules) are determined at high precision from the…

cs.CV2019

SinGAN: Learning a Generative Model from a Single Natural Image

Tamar Rott Shaham, Tali Dekel, Tomer Michaeli

We introduce SinGAN, an unconditional generative model that can be learned from a single natural image. Our model is trained to capture the internal distribution of patches within…

cs.LG2019★ 60 cited

Rethinking Lossy Compression: The Rate-Distortion-Perception Tradeoff

Yochai Blau, Tomer Michaeli

Lossy compression algorithms are typically designed and analyzed through the lens of Shannon's rate-distortion theory, where the goal is to achieve the lowest possible distortion (…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.