no code implementations • 14 Aug 2023 • Yochai Blau, Rohan Agrawal, Lior Madmony, Gary Wang, Andrew Rosenberg, Zhehuai Chen, Zorik Gekhman, Genady Beryozkin, Parisa Haghani, Bhuvana Ramabhadran
We use text-injection to improve the recognition of PII categories by including fake textual substitutes of PII categories in the training data using a text injection method.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • NeurIPS 2021 • Regev Cohen, Yochai Blau, Daniel Freedman, Ehud Rivlin
In this work, we introduce image denoisers derived as the gradients of smooth scalar-valued deep neural networks, acting as potentials.
no code implementations • 23 Jan 2020 • Daniel Freedman, Yochai Blau, Liran Katzir, Amit Aides, Ilan Shimshoni, Danny Veikherman, Tomer Golany, Ariel Gordon, Greg Corrado, Yossi Matias, Ehud Rivlin
Our coverage algorithm is the first such algorithm to be evaluated in a large-scale way; while our depth estimation technique is the first calibration-free unsupervised method applied to colonoscopies.
no code implementations • ICLR 2019 • Adar Elad, Doron Haviv, Yochai Blau, Tomer Michaeli
The recently proposed information bottleneck (IB) theory of deep nets suggests that during training, each layer attempts to maximize its mutual information (MI) with the target labels (so as to allow good prediction accuracy), while minimizing its MI with the input (leading to effective compression and thus good generalization).
no code implementations • 23 Jan 2019 • 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 (e. g., low MSE or high SSIM) at any given bit rate.
8 code implementations • 20 Sep 2018 • Yochai Blau, Roey Mechrez, Radu Timofte, Tomer Michaeli, Lihi Zelnik-Manor
This paper reports on the 2018 PIRM challenge on perceptual super-resolution (SR), held in conjunction with the Perceptual Image Restoration and Manipulation (PIRM) workshop at ECCV 2018.
Ranked #33 on Video Quality Assessment on MSU SR-QA Dataset
1 code implementation • CVPR 2018 • Yochai Blau, Tomer Michaeli
Image restoration algorithms are typically evaluated by some distortion measure (e. g. PSNR, SSIM, IFC, VIF) or by human opinion scores that quantify perceived perceptual quality.
no code implementations • 11 Dec 2016 • Yochai Blau, Tomer Michaeli
Our approach relies on replacing the orthogonality constraints underlying those methods by unpredictability constraints.