Relevant publications

E. Schwartz, A. M. Bronstein, R. Giryes, ISP distillation, IEEE Open Journal of Signal Processing 4, 12-20, 2023 details

A. Arbelle, S. Doveh, A. Alfassy, J. Shtok, G. Lev, E. Schwartz, H. Kuehne, H. Barak Levi, P. Sattigeri, R. Panda, C.-F. Chen, A. M. Bronstein, K. Saenko, S. Ullman, R. Giryes, R. Feris, L. Karlinsky, Detector-free weakly supervised grounding by separation, Proc. CVPR, 2022 details

S. Doveh, E. Schwartz, C. Xue, R. Feris, A. M. Bronstein, R. Giryes, L. Karlinsky, MetAdapt: Meta-learned task-adaptive architecture for few-shot classification, Pattern Recognition Letters, 2021 details

L. Karlinsky, J. Shtok, A. Alfassy, M. Lichtenstein, S. Harary, E. Schwartz, S. Doveh, P. Sattigeri, R. Feris, A. M. Bronstein, R. Giryes, StarNet: towards weakly supervised few-shot detection and explainable few-shot classification, Proc. AAAI, 2021 details

C. Baskin, E. Schwartz, E. Zheltonozhskii, N. Liss, R. Giryes, A. M. Bronstein, A. Mendelson, UNIQ: Uniform noise injection for non-uniform quantization of neural networks, ACM Transactions on Computer Systems (TOCS), 2020 details

S. Doveh, E. Schwartz, C. Xue, R. Feris, A. M. Bronstein, R. Giryes, L. Karlinsky, MetAdapt: Meta-learned task-adaptive architecture for few-shot classification, arXiv: 1912.00412, 2019 details

E. Schwartz, L. Karlinsky, J. Shtok, S. Harary, M. Marder, R. Feris, A. Kumar, R. Giryes, A. M. Bronstein, RepMet: Representative-based metric learning for classification and one-shot object detection, Proc. Computer Vision and Pattern Recognition (CVPR), 2019 details

E. Schwartz, L. Karlinsky, R. Feris, R. Giryes, A. M. Bronstein, Baby steps towards few-shot learning with multiple semantics, arXiv:1906.01905, 2019 details

N. Diamant, D. Zadok, C. Baskin, E. Schwartz, A. M. Bronstein, Beholder-GAN: Generation and beautification of facial images with conditioning on their beauty level, Proc. Int'l Conf. on Image Processing (ICIP), 2019 details

E. Schwartz, L. Karlinsky, J. Shtok, S. Harary, M. Marder, R. Feris, A. Kumar, R. Giryes, A. M. Bronstein, ∆-encoder: an effective sample synthesis method for few-shot object recognition, Proc. Neural Information Processing Systems (NIPS), 2018 details

C. Baskin, N. Liss, Y. Chai, E. Zheltonozhskii, E. Schwartz, R. Giryes, A. Mendelson, A. M. Bronstein, NICE: noise injection and clamping estimation for neural network quantization, arXiv:1810.00162, 2018 details

E. Schwartz, R. Giryes, A. M. Bronstein, DeepISP: Towards learning an end-to-end image processing pipeline, IEEE Trans. on Image Processing, 2018 details