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