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Caner Hazırbaş

Caner Hazırbaş

Scientific Employee

Technische Universität München

Department of Computer Science
Informatik 9
Boltzmannstrasse 3
85748 Garching

Tel: +49-89-289-17788
Fax: +49-89-289-17757
Office: 02.09.041

Brief Bio

My personal webpage:

Google Scholar : h-index: 4, citations: 227

Research Interests

Deep Learning, Object Recognition/Detection and Semantic Scene Understanding.


Conference and Workshop Papers
Deep Depth From Focus (Caner Hazirbas, Laura Leal-Taixé, Daniel Cremers), In ArXiv preprint arXiv:1704.01085, 2017. ([arxiv]) [bib]
Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems (Tim Meinhardt, Michael Möller, Caner Hazirbas, Daniel Cremers), In ArXiv preprint arXiv:1704.03488, 2017. ([arxiv]) [bib]
Image-based localization using LSTMs for structured feature correlation (Florian Walch, Caner Hazirbas, Laura Leal-Taixé, Torsten Sattler, Sebastian Hilsenbeck, Daniel Cremers), In ArXiv preprint 1611.07890, 2016. ([arxiv]) [bib]
FuseNet: Incorporating Depth into Semantic Segmentation via Fusion-based CNN Architecture (C. Hazirbas, L. Ma, C. Domokos, D. Cremers), In Asian Conference on Computer Vision, 2016. ([code]) [bib] [pdf]
CAPTCHA Recognition with Active Deep Learning (F. Stark, C. Hazirbas, R. Triebel, D. Cremers), In GCPR Workshop on New Challenges in Neural Computation, 2015. ([code]) [bib] [pdf]
FlowNet: Learning Optical Flow with Convolutional Networks (A. Dosovitskiy, P. Fischer, E. Ilg, P. Haeusser, 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]
Optimizing the Relevance-Redundancy Tradeoff for Efficient Semantic Segmentation (C. Hazirbas, J. Diebold, D. Cremers), In Scale Space and Variational Methods in Computer Vision (SSVM), 2015. ([code]) [bib] [pdf] [doi]Oral Presentation
Interactive Multi-label Segmentation of RGB-D Images (J. Diebold, N. Demmel, C. Hazirbas, M. Möller, D. Cremers), In Scale Space and Variational Methods in Computer Vision (SSVM), 2015. ([code]) [bib] [pdf] [doi]
Masters Thesis
Feature Selection and Learning for Semantic Segmentation (Caner Hazirbas), Master's thesis, Technical University Munich, 2014. [bib] [pdf]
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Last edited 10.05.2017 16:43 by Caner Hazirbas