| Delta-encoder: an effective sample synthesis method for few-shot object recognition E Schwartz, L Karlinsky, J Shtok, S Harary, M Marder, R Feris, A Kumar, ... Neural Information Processing Systems, 2018 | 115 | 2018 |
| RepMet: Representative-based metric learning for classification and few-shot object detection L Karlinsky, J Shtok, S Harary, E Schwartz, A Aides, R Feris, R Giryes, ... Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 82 | 2019 |
| DeepISP: Toward learning an end-to-end image processing pipeline E Schwartz, R Giryes, AM Bronstein IEEE Transactions on Image Processing 28 (2), 912-923, 2018 | 67 | 2018 |
| Uniq: Uniform noise injection for non-uniform quantization of neural networks C Baskin, E Schwartz, E Zheltonozhskii, N Liss, R Giryes, AM Bronstein, ... arXiv preprint arXiv:1804.10969, 2018 | 32 | 2018 |
| Nice: Noise injection and clamping estimation for neural network quantization C Baskin, N Liss, Y Chai, E Zheltonozhskii, E Schwartz, R Giryes, ... arXiv preprint arXiv:1810.00162, 2018 | 28 | 2018 |
| Baby steps towards few-shot learning with multiple semantics E Schwartz, L Karlinsky, R Feris, R Giryes, AM Bronstein arXiv preprint arXiv:1906.01905, 2019 | 22 | 2019 |
| RepMet: Representative-based metric learning for classification and one-shot object detection E Schwartz, L Karlinsky, J Shtok, S Harary, M Marder, S Pankanti, R Feris, ... arXiv preprint arXiv:1806.04728, 2018 | 16 | 2018 |
| Uniq: Uniform noise injection for the quantization of neural networks C Baskin, E Schwartz, E Zheltonozhskii, N Liss, R Giryes, AM Bronstein, ... arXiv preprint arXiv:1804.10969 3, 2018 | 16 | 2018 |
| DeepISP: learning end-to-end image processing pipeline E Schwartz, R Giryes, AM Bronstein | 14 | 2018 |
| Beholder-gan: Generation and beautification of facial images with conditioning on their beauty level N Diamant, D Zadok, C Baskin, E Schwartz, AM Bronstein 2019 IEEE International Conference on Image Processing (ICIP), 739-743, 2019 | 8 | 2019 |
| StarNet: towards weakly supervised few-shot detection and explainable few-shot classification L Karlinsky, J Shtok, A Alfassy, M Lichtenstein, S Harary, E Schwartz, ... arXiv preprint arXiv:2003.06798, 2020 | 3 | 2020 |
| MetAdapt: Meta-Learned Task-Adaptive Architecture for Few-Shot Classification S Doveh, E Schwartz, C Xue, R Feris, A Bronstein, R Giryes, L Karlinsky arXiv preprint arXiv:1912.00412, 2019 | 3 | 2019 |
| Imaging devices and methods for authenticating a user E Shalev, S Katz, E Schwartz US Patent App. 14/995,025, 2017 | 2 | 2017 |
| UNIQ: Uniform Noise Injection for Non-Uniform Quantization of Neural Networks C Baskin, N Liss, E Schwartz, E Zheltonozhskii, R Giryes, AM Bronstein, ... ACM Transactions on Computer Systems (TOCS) 37 (1--4), 1-15, 2021 | | 2021 |
| ISP Distillation E Schwartz, A Bronstein, R Giryes arXiv preprint arXiv:2101.10203, 2021 | | 2021 |
| Fine-grained Angular Contrastive Learning with Coarse Labels G Bukchin, E Schwartz, K Saenko, O Shahar, R Feris, R Giryes, ... arXiv preprint arXiv:2012.03515, 2020 | | 2020 |
| Representative-based metric learning for classification and few-shot object detection L Karlinsky, E Schwartz, J Shtok, M Marder, S Harary US Patent 10,832,096, 2020 | | 2020 |
| Out-of-sample generating few-shot classification networks L Karlinsky, M Marder, E Schwartz, J Shtok, S Harary US Patent 10,796,203, 2020 | | 2020 |
| Method and system for end-to-end image processing E Schwartz, R Giryes, A Bronstein US Patent App. 16/251,123, 2020 | | 2020 |
| Abhishek Kumar A Kumar Proceedings of the National Academy of Sciences, India Section A: Physical …, 0 | | |
Alex BronsteinTechnion, Department of Computer ScienceVerified email at technion.ac.il
