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Philip Häusser

Philip Häusser

M.Sc.

Technische Universität München

Department of Computer Science
Informatik 9
Boltzmannstrasse 3
85748 Garching
Germany

Tel: +49-89-289-17788
Fax: +49-89-289-17757
Office: 02.09.041
Mail: haeusser@cs.tum.edu

I am currently on leave from TUM, working as a Research Software Engineer Intern at Google.

About

I'm a second-year PhD student in computer science at TUM, doing research in computer vision and machine learning advised by Prof. Daniel Cremers. My current projects focus on the application of convolutional neural networks (CNNs) on tasks like optical anomaly detection and scene recognition. Research interests include: computer vision, machine learning, deep learning, convolutional networks, optical flow, scene flow, facial expression recognition

I hold a Master's degree in physics from the University of California, Santa Cruz (USA) and a Bachelor's degree in physics from the LMU Munich where I was working at the cavity quantum optics group headed by Prof. T.W. Haensch.

When I'm not in the lab you might find me playing squash or volleyball or you might encounter one of my TV productions.

Teaching

Summer Term 2015

Summer Term 2016

Publications

Conference and Workshop Papers
2016
A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation (N.Mayer, E.Ilg, P.Häusser, P.Fischer, D.Cremers, A.Dosovitskiy, T.Brox), In IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2016. (arXiv:1512.02134) [bib] [pdf]
2015
FlowNet: Learning Optical Flow with Convolutional Networks (A. Dosovitskiy, P. Fischer, E. Ilg, P. Häusser, C. Hazirbas, V. Golkov, P. van der Smagt, D. Cremers, T. Brox), In IEEE International Conference on Computer Vision (ICCV), 2015. ([video],[code]) [bib] [pdf] [doi]
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Last edited 04.06.2016 04:04 by Philip Haeusser