Our paper "End-to-End Learning for Image Burst Deblurring" has been accepted as an oral at ACCV 2016. A preprint version of our work can be found on arXiv here.
I am now leading the Computational Imaging Group in the Department of Empirical Inference at the Max Planck Institute for Intelligent Systems in Tübingen.
I am interested in a wide range of signal and image processing problems in scientific imaging as well as computational photography. My particular interest is on physical modeling and the development of efficient and novel inference schemes for inverse problems.
Please do visit our group page for more information on our research.
Gauci, A., Abela, J., Cachia, E., Hirsch, M., ZarbAdami, K.
Proc. SPIE 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016), pages: 1022511, (Editors: Yulin Wang, Tuan D. Pham, Vit Vozenilek, David Zhang, Yi Xie), 2017 (conference)
IEEE International Conference on Computer Vision (ICCV 2015), Workshop on Inverse Rendering, 2015, Note: This work has been presented as a poster and is not included in the workshop proceedings. (poster)
Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems