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Home Members Caner Hazırbaş

Caner Hazırbaş

AlumniTechnische Universität München

Department of Computer Science
Informatik 9
Boltzmannstrasse 3
85748 Garching
Germany

Fax: +49-89-289-17757
Office: 
Mail: caner@hazirbas.com

My personal webpage: hazirbas.com

Google Scholar : i10-index: 8, h-index: 8, citations: 2612

Publications


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Journal Articles
2018
[]What Makes Good Synthetic Training Data for Learning Disparity and Optical Flow Estimation? (Nikolaus Mayer, Eddy Ilg, Philipp Fischer, Caner Hazirbas, Daniel Cremers, Alexey Dosovitskiy and Thomas Brox), In , volume 41, 2018. (arxiv) [bibtex] [arXiv:1801.06397]
Conference and Workshop Papers
2018
[]Deep Depth From Focus (C. Hazirbas, S. G. Soyer, M. C. Staab, L. Leal-Taixé and D. Cremers), In Asian Conference on Computer Vision (ACCV), 2018. ([arxiv], Deep Depth From Focus,[dataset]) [bibtex]
2017
[]Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems (T. Meinhardt, M. Moeller, C. Hazirbas and D. Cremers), In IEEE International Conference on Computer Vision (ICCV), 2017. ([arxiv], [code]) [bibtex]
[]Image-based localization using LSTMs for structured feature correlation (F. Walch, C. Hazirbas, L. Leal-Taixé, T. Sattler, S. Hilsenbeck and D. Cremers), In IEEE International Conference on Computer Vision (ICCV), 2017. ([arxiv]) [bibtex]
2016
[]FuseNet: Incorporating Depth into Semantic Segmentation via Fusion-based CNN Architecture (C. Hazirbas, L. Ma, C. Domokos and D. Cremers), In Asian Conference on Computer Vision, 2016. ([code]) [bibtex] [pdf]
2015
[]CAPTCHA Recognition with Active Deep Learning (F. Stark, C. Hazirbas, R. Triebel and D. Cremers), In GCPR Workshop on New Challenges in Neural Computation, 2015. ([code]) [bibtex] [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 and T. Brox), In IEEE International Conference on Computer Vision (ICCV), 2015. ([video],[code]) [bibtex] [doi] [pdf]
[]Optimizing the Relevance-Redundancy Tradeoff for Efficient Semantic Segmentation (C. Hazirbas, J. Diebold and D. Cremers), In Scale Space and Variational Methods in Computer Vision (SSVM), 2015. ([code]) [bibtex] [doi] [pdf]Oral Presentation
[]Interactive Multi-label Segmentation of RGB-D Images (J. Diebold, N. Demmel, C. Hazirbas, M. Möller and D. Cremers), In Scale Space and Variational Methods in Computer Vision (SSVM), 2015. ([code]) [bibtex] [doi] [pdf]
Other Publications
2014
[]Feature Selection and Learning for Semantic Segmentation (Caner Hazirbas), Master's thesis, Technical University Munich, 2014.  [bibtex] [pdf]
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Rechte Seite

Informatik IX
Chair of Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching

info@vision.in.tum.de