Broadly speaking, the lab research is at the intersection between the fields of signal and image processing, and machine learning. More specifically, our interests include, but are not limited to, deep learning, sparse representations, low dimensional signal modeling, computational imaging, compressed sensing, and inverse problems.
Some of the lab recent works include (i) a new fidelity term for solving inverse problems with an advanced strategy to use GANs as priors by training them on the target data (ii) a neural network for 3D meshes; (iii) a correction filter that allows using super-resolution neural networks with any down-sampling kernel (CVPR 2020 award nominee); (iv) deep learning-based optical design for all-in-focus imaging and single-lens depth reconstruction (first place in the OSA optical element of the future grand student challenge); (v) new few-shot learning tools for image classification, object detection, multi-label images, interpretable weakly supervised detection and self-supervised based fine-class classification; (vi) a deep neural network that replaces the conventional image signal processing (ISP) pipeline; (vii) novel adversarial robustness and detection approaches; (viii) theoretical analysis of neural network, e.g., by studying their margin-based generalization, smoothness impact on expressivity and generalization and using tools from signal processing.
The PI Raja Giryes
Raja Giryes is an associate professor in the school of electrical engineering at Tel Aviv University. He received the B.Sc (2007), M.Sc. (supervision by Prof. M. Elad and Prof. Y. C. Eldar, 2009), and Ph.D. (supervision by Prof. M. Elad, 2014) degrees from the Department of Computer Science, The Technion - Israel Institute of Technology, Haifa. Raja was a postdoc at the computer science department at the Technion (Nov. 2013 till July 2014) and at the lab of Prof. G. Sapiro at Duke University, Durham, USA (July 2014 and Aug. 2015). His research interests lie at the intersection between signal and image processing and machine learning, and in particular, in deep learning, inverse problems, sparse representations, computational photography, and signal and image modeling. Raja received the EURASIP best P.hD. award, the ERC-StG grant, Maof prize for excellent young faculty (2016-2019), VATAT scholarship for excellent postdoctoral fellows (2014-2015), Intel Research and Excellence Award (2005, 2013), the Excellence in Signal Processing Award (ESPA) from Texas Instruments (2008) and was part of the Azrieli Fellows program (2010-2013). He has organized workshops and tutorials on deep learning theory in various conferences including ICML, CVPR, and ICCV. He serves as a consultant in various high-tech companies including Innoviz technologies.