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20172021
most citedEfficient Deformable Shape Correspondence via Kernel Matching

25 citations · 36 across the 5 of their papers we have counts for

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cs.CV2021

Unsupervised High-Fidelity Facial Texture Generation and Reconstruction

Ron Slossberg, Ibrahim Jubran, Ron Kimmel

Many methods have been proposed over the years to tackle the task of facial 3D geometry and texture recovery from a single image. Such methods often fail to provide high-fidelity t…

cs.CV20201 cited

On Calibration of Scene-Text Recognition Models

Ron Slossberg, Oron Anschel, Amir Markovitz +6

In this work, we study the problem of word-level confidence calibration for scene-text recognition (STR). Although the topic of confidence calibration has been an active research a…

cs.CV2020

Sequence-to-Sequence Contrastive Learning for Text Recognition

Aviad Aberdam, Ron Litman, Shahar Tsiper +5

We propose a framework for sequence-to-sequence contrastive learning (SeqCLR) of visual representations, which we apply to text recognition. To account for the sequence-to-sequence…

cs.CV201725 cited

Efficient Deformable Shape Correspondence via Kernel Matching

Zorah Lähner, Matthias Vestner, Amit Boyarski +8

We present a method to match three dimensional shapes under non-isometric deformations, topology changes and partiality. We formulate the problem as matching between a set of pair-…

cs.CV20174 cited

Deep Stereo Matching with Dense CRF Priors

Ron Slossberg, Aaron Wetzler, Ron Kimmel

Stereo reconstruction from rectified images has recently been revisited within the context of deep learning. Using a deep Convolutional Neural Network to obtain patch-wise matching…