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ORCIDEli Schwartz
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2020 – today
- 2024
[j5]Eli Schwartz
, Assaf Arbelle, Leonid Karlinsky, Sivan Harary, Florian Scheidegger, Sivan Doveh, Raja Giryes:
MAEDAY: MAE for few- and zero-shot AnomalY-Detection. Comput. Vis. Image Underst. 241: 103958 (2024)- [c11]Nimrod Shabtay, Eli Schwartz, Raja Giryes:
Deep Phase Coded Image Prior. ICCP 2024: 1-12 - [i19]Eli Schwartz, Leshem Choshen, Joseph Shtok, Sivan Doveh, Leonid Karlinsky, Assaf Arbelle:
NumeroLogic: Number Encoding for Enhanced LLMs' Numerical Reasoning. CoRR abs/2404.00459 (2024) - [i18]Nimrod Shabtay, Eli Schwartz, Raja Giryes:
Deep Phase Coded Image Prior. CoRR abs/2404.03906 (2024) - 2023
- [c10]Sivan Doveh, Assaf Arbelle, Sivan Harary, Eli Schwartz, Roei Herzig, Raja Giryes, Rogério Feris, Rameswar Panda, Shimon Ullman, Leonid Karlinsky:
Teaching Structured Vision & Language Concepts to Vision & Language Models. CVPR 2023: 2657-2668 - [c9]Daniel M. Lang, Eli Schwartz, Cosmin I. Bercea, Raja Giryes, Julia A. Schnabel:
Multispectral 3D Masked Autoencoders for Anomaly Detection in Non-Contrast Enhanced Breast MRI. CaPTion@MICCAI 2023: 55-67 - 2022
- [j4]Eli Schwartz, Leonid Karlinsky, Rogério Feris, Raja Giryes, Alexander M. Bronstein:
Baby steps towards few-shot learning with multiple semantics. Pattern Recognit. Lett. 160: 142-147 (2022) - [c8]Sivan Harary, Eli Schwartz, Assaf Arbelle, Peter W. J. Staar, Shady Abu-Hussein, Elad Amrani, Roei Herzig, Amit Alfassy, Raja Giryes, Hilde Kuehne, Dina Katabi, Kate Saenko, Rogério Feris, Leonid Karlinsky:
Unsupervised Domain Generalization by Learning a Bridge Across Domains. CVPR 2022: 5270-5280 - [c7]Amit Alfassy, Assaf Arbelle, Oshri Halimi, Sivan Harary, Roei Herzig, Eli Schwartz, Rameswar Panda, Michele Dolfi, Christoph Auer, Peter W. J. Staar, Kate Saenko, Rogério Feris, Leonid Karlinsky:
FETA: Towards Specializing Foundational Models for Expert Task Applications. NeurIPS 2022 - [i17]Amit Alfassy, Assaf Arbelle, Oshri Halimi, Sivan Harary, Roei Herzig, Eli Schwartz, Rameswar Panda, Michele Dolfi, Christoph Auer, Kate Saenko, Peter W. J. Staar, Rogério Feris, Leonid Karlinsky:
FETA: Towards Specializing Foundation Models for Expert Task Applications. CoRR abs/2209.03648 (2022) - [i16]Sivan Doveh, Assaf Arbelle, Sivan Harary, Rameswar Panda, Roei Herzig, Eli Schwartz, Donghyun Kim, Raja Giryes, Rogério Feris, Shimon Ullman, Leonid Karlinsky:
Teaching Structured Vision&Language Concepts to Vision&Language Models. CoRR abs/2211.11733 (2022) - [i15]Nimrod Shabtay, Eli Schwartz, Raja Giryes:
PIP: Positional-encoding Image Prior. CoRR abs/2211.14298 (2022) - [i14]Eli Schwartz, Assaf Arbelle, Leonid Karlinsky, Sivan Harary, Florian Scheidegger, Sivan Doveh, Raja Giryes:
MAEDAY: MAE for few and zero shot AnomalY-Detection. CoRR abs/2211.14307 (2022) - 2021
- [j3]Sivan Doveh, Eli Schwartz, Chao Xue, Rogério Feris, Alexander M. Bronstein, Raja Giryes, Leonid Karlinsky:
MetAdapt: Meta-learned task-adaptive architecture for few-shot classification. Pattern Recognit. Lett. 149: 130-136 (2021) - [c6]Leonid Karlinsky, Joseph Shtok, Amit Alfassy, Moshe Lichtenstein, Sivan Harary, Eli Schwartz, Sivan Doveh, Prasanna Sattigeri, Rogério Feris, Alex M. Bronstein, Raja Giryes:
StarNet: towards Weakly Supervised Few-Shot Object Detection. AAAI 2021: 1743-1753 - [c5]Guy Bukchin, Eli Schwartz, Kate Saenko, Ori Shahar, Rogério Feris, Raja Giryes, Leonid Karlinsky:
Fine-Grained Angular Contrastive Learning With Coarse Labels. CVPR 2021: 8730-8740 - [c4]Assaf Arbelle, Sivan Doveh, Amit Alfassy, Joseph Shtok, Guy Lev, Eli Schwartz, Hilde Kuehne, Hila Barak Levi, Prasanna Sattigeri, Rameswar Panda, Chun-Fu Chen, Alex M. Bronstein, Kate Saenko, Shimon Ullman, Raja Giryes, Rogério Feris, Leonid Karlinsky:
Detector-Free Weakly Supervised Grounding by Separation. ICCV 2021: 1781-1792 - [i13]Eli Schwartz, Alex M. Bronstein, Raja Giryes:
ISP Distillation. CoRR abs/2101.10203 (2021) - [i12]Assaf Arbelle, Sivan Doveh, Amit Alfassy, Joseph Shtok, Guy Lev, Eli Schwartz, Hilde Kuehne, Hila Barak Levi, Prasanna Sattigeri, Rameswar Panda, Chun-Fu Chen, Alex M. Bronstein, Kate Saenko, Shimon Ullman, Raja Giryes, Rogério Feris, Leonid Karlinsky:
Detector-Free Weakly Supervised Grounding by Separation. CoRR abs/2104.09829 (2021) - [i11]Sivan Harary, Eli Schwartz, Assaf Arbelle, Peter W. J. Staar, Shady Abu-Hussein, Elad Amrani, Roei Herzig, Amit Alfassy, Raja Giryes, Hilde Kuehne, Dina Katabi, Kate Saenko, Rogério Feris, Leonid Karlinsky:
Unsupervised Domain Generalization by Learning a Bridge Across Domains. CoRR abs/2112.02300 (2021) - 2020
- [i10]Leonid Karlinsky, Joseph Shtok, Amit Alfassy, Moshe Lichtenstein, Sivan Harary, Eli Schwartz, Sivan Doveh, Prasanna Sattigeri, Rogério Schmidt Feris, Alexander M. Bronstein, Raja Giryes:
StarNet: towards weakly supervised few-shot detection and explainable few-shot classification. CoRR abs/2003.06798 (2020) - [i9]Guy Bukchin, Eli Schwartz, Kate Saenko, Ori Shahar, Rogério Feris, Raja Giryes, Leonid Karlinsky:
Fine-grained Angular Contrastive Learning with Coarse Labels. CoRR abs/2012.03515 (2020)
2010 – 2019
- 2019
- [j2]Eli Schwartz, Raja Giryes, Alexander M. Bronstein:
DeepISP: Toward Learning an End-to-End Image Processing Pipeline. IEEE Trans. Image Process. 28(2): 912-923 (2019) - [j1]Chaim Baskin, Natan Liss, Eli Schwartz, Evgenii Zheltonozhskii, Raja Giryes, Alex M. Bronstein, Avi Mendelson:
UNIQ: Uniform Noise Injection for Non-Uniform Quantization of Neural Networks. ACM Trans. Comput. Syst. 37(1-4): 4:1-4:15 (2019) - [c3]Leonid Karlinsky, Joseph Shtok, Sivan Harary, Eli Schwartz, Amit Aides, Rogério Schmidt Feris, Raja Giryes, Alexander M. Bronstein:
RepMet: Representative-Based Metric Learning for Classification and Few-Shot Object Detection. CVPR 2019: 5197-5206 - [c2]Nir Diamant, Dean Zadok, Chaim Baskin, Eli Schwartz, Alexander M. Bronstein:
Beholder-Gan: Generation and Beautification of Facial Images with Conditioning on Their Beauty Level. ICIP 2019: 739-743 - [i8]Nir Diamant, Dean Zadok, Chaim Baskin, Eli Schwartz, Alexander M. Bronstein:
Beholder-GAN: Generation and Beautification of Facial Images with Conditioning on Their Beauty Level. CoRR abs/1902.02593 (2019) - [i7]Eli Schwartz, Leonid Karlinsky, Rogério Schmidt Feris, Raja Giryes, Alexander M. Bronstein:
Baby steps towards few-shot learning with multiple semantics. CoRR abs/1906.01905 (2019) - [i6]Sivan Doveh, Eli Schwartz, Chao Xue, Rogério Schmidt Feris, Alexander M. Bronstein, Raja Giryes, Leonid Karlinsky:
MetAdapt: Meta-Learned Task-Adaptive Architecture for Few-Shot Classification. CoRR abs/1912.00412 (2019) - 2018
- [c1]Eli Schwartz, Leonid Karlinsky, Joseph Shtok, Sivan Harary, Mattias Marder, Abhishek Kumar, Rogério Schmidt Feris, Raja Giryes, Alexander M. Bronstein:
Delta-encoder: an effective sample synthesis method for few-shot object recognition. NeurIPS 2018: 2850-2860 - [i5]Eli Schwartz, Raja Giryes, Alexander M. Bronstein:
DeepISP: Learning End-to-End Image Processing Pipeline. CoRR abs/1801.06724 (2018) - [i4]Chaim Baskin, Eli Schwartz, Evgenii Zheltonozhskii, Natan Liss, Raja Giryes, Alexander M. Bronstein, Avi Mendelson:
UNIQ: Uniform Noise Injection for the Quantization of Neural Networks. CoRR abs/1804.10969 (2018) - [i3]Eli Schwartz, Leonid Karlinsky, Joseph Shtok, Sivan Harary, Mattias Marder, Sharathchandra Pankanti, Rogério Schmidt Feris, Abhishek Kumar, Raja Giryes, Alexander M. Bronstein:
RepMet: Representative-based metric learning for classification and one-shot object detection. CoRR abs/1806.04728 (2018) - [i2]Eli Schwartz, Leonid Karlinsky, Joseph Shtok, Sivan Harary, Mattias Marder, Rogério Schmidt Feris, Abhishek Kumar, Raja Giryes, Alexander M. Bronstein:
Delta-encoder: an effective sample synthesis method for few-shot object recognition. CoRR abs/1806.04734 (2018) - [i1]Chaim Baskin, Natan Liss, Yoav Chai, Evgenii Zheltonozhskii, Eli Schwartz, Raja Giryes, Avi Mendelson, Alexander M. Bronstein:
NICE: Noise Injection and Clamping Estimation for Neural Network Quantization. CoRR abs/1810.00162 (2018)
Coauthor Index
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