10 citations · 18 across the 3 of their papers we have counts for
4 papers
Solving ImageNet: a Unified Scheme for Training any Backbone to Top Results
Tal Ridnik, Hussam Lawen, Emanuel Ben-Baruch +1
ImageNet serves as the primary dataset for evaluating the quality of computer-vision models. The common practice today is training each architecture with a tailor-made scheme, desi…
It's All in the Head: Representation Knowledge Distillation through Classifier Sharing
Emanuel Ben-Baruch, Matan Karklinsky, Yossi Biton +3
Representation knowledge distillation aims at transferring rich information from one model to another. Common approaches for representation distillation mainly focus on the direct…
TResNet: High Performance GPU-Dedicated Architecture
Tal Ridnik, Hussam Lawen, Asaf Noy +3
Many deep learning models, developed in recent years, reach higher ImageNet accuracy than ResNet50, with fewer or comparable FLOPS count. While FLOPs are often seen as a proxy for…
Compact Network Training for Person ReID
Hussam Lawen, Avi Ben-Cohen, Matan Protter +2
The task of person re-identification (ReID) has attracted growing attention in recent years leading to improved performance, albeit with little focus on real-world applications. Mo…