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Faculty of Informatics
Technical University of Munich

Technical University of Munich

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Home Members Caner Hazırbaş

Caner Hazırbaş

PhD StudentTechnische 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: hazirbas@cs.tum.edu

My personal webpage: hazirbas.com

Google Scholar : h-index: 5, citations: 440

Publications

Conference and Workshop Papers
2017
Deep Depth From Focus (Caner Hazirbas, Laura Leal-Taixé, Daniel Cremers), In ArXiv preprint arXiv:1704.01085, 2017.([arxiv], [dataset]) [bib]
Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems (Tim Meinhardt, Michael Moeller, Caner Hazirbas, Daniel Cremers), In IEEE International Conference on Computer Vision (ICCV), 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 IEEE International Conference on Computer Vision (ICCV), 2017.([arxiv]) [bib]
2016
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]
2015
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
2014
Feature Selection and Learning for Semantic Segmentation (Caner Hazirbas), Master's thesis, Technical University Munich, 2014. [bib] [pdf]
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Rechte Seite

Informatik IX
Chair for Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching

info@vision.in.tum.de