11 citations · 11 across the 3 of their papers we have counts for
4 papers
Minimizing Embedding Distortion for Robust Out-of-Distribution Performance
Tom Shaked, Yuval Goldman, Oran Shayer
Foundational models, trained on vast and diverse datasets, have demonstrated remarkable capabilities in generalizing across different domains and distributions for various zero-sho…
Enhancing Generic Segmentation with Learned Region Representations
Or Isaacs, Oran Shayer, Michael Lindenbaum
Current successful approaches for generic (non-semantic) segmentation rely mostly on edge detection and have leveraged the strengths of deep learning mainly by improving the edge d…
Learning Pixel Representations for Generic Segmentation
Oran Shayer, Michael Lindenbaum
Deep learning approaches to generic (non-semantic) segmentation have so far been indirect and relied on edge detection. This is in contrast to semantic segmentation, where DNNs are…
Learning Discrete Weights Using the Local Reparameterization Trick
Oran Shayer, Dan Levi, Ethan Fetaya
Recent breakthroughs in computer vision make use of large deep neural networks, utilizing the substantial speedup offered by GPUs. For applications running on limited hardware, how…