1 code implementation • 18 Jan 2022 • Emanuel Ben-Baruch, Matan Karklinsky, Yossi Biton, Avi Ben-Cohen, Hussam Lawen, Nadav Zamir
Such direct methods may be limited in transferring high-order dependencies embedded in the representation vectors, or in handling the capacity gap between the teacher and student models.
Ranked #1 on Face Verification on IJB-C
1 code implementation • CVPR 2022 • Emanuel Ben-Baruch, Tal Ridnik, Itamar Friedman, Avi Ben-Cohen, Nadav Zamir, Asaf Noy, Lihi Zelnik-Manor
We propose to estimate the class distribution using a dedicated temporary model, and we show its improved efficiency over a naive estimation computed using the dataset's partial annotations.
Ranked #1 on Multi-Label Classification on OpenImages-v6
1 code implementation • 26 Sep 2021 • Tamar Glaser, Emanuel Ben-Baruch, Gilad Sharir, Nadav Zamir, Asaf Noy, Lihi Zelnik-Manor
We address this gap with a tailor-made solution, combining the power of CNNs for image representation and transformers for album representation to perform global reasoning on image collection, offering a practical and efficient solution for photo albums event recognition.
1 code implementation • ICCV 2021 • Avi Ben-Cohen, Nadav Zamir, Emanuel Ben Baruch, Itamar Friedman, Lihi Zelnik-Manor
We argue that using a single embedding vector to represent an image, as commonly practiced, is not sufficient to rank both relevant seen and unseen labels accurately.
Ranked #3 on Multi-label zero-shot learning on Open Images V4
5 code implementations • ICCV 2021 • Emanuel Ben-Baruch, Tal Ridnik, Nadav Zamir, Asaf Noy, Itamar Friedman, Matan Protter, Lihi Zelnik-Manor
In this paper, we introduce a novel asymmetric loss ("ASL"), which operates differently on positive and negative samples.
Ranked #4 on Multi-Label Classification on NUS-WIDE
1 code implementation • 8 Apr 2019 • Asaf Noy, Niv Nayman, Tal Ridnik, Nadav Zamir, Sivan Doveh, Itamar Friedman, Raja Giryes, Lihi Zelnik-Manor
In this paper, we propose a differentiable search space that allows the annealing of architecture weights, while gradually pruning inferior operations.