| Deblurgan: Blind motion deblurring using conditional adversarial networks O Kupyn, V Budzan, M Mykhailych, D Mishkin, J Matas Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 1219 | 2018 |
| All you need is a good init D Mishkin, J Matas International Conference on Learning Representations, 2016, 2016 | 661 | 2016 |
| Working hard to know your neighbor's margins: Local descriptor learning loss A Mishchuk, D Mishkin, F Radenovic, J Matas Advances in Neural Information Processing Systems, 4826-4837, 2017 | 506 | 2017 |
| Systematic Evaluation of Convolution Neural Network Advances on the ImageNet D Mishkin, N Sergievskiy, J Matas Computer Vision and Image Understanding, 2017 | 356 | 2017 |
| Kornia: an open source differentiable computer vision library for pytorch E Riba, D Mishkin, D Ponsa, E Rublee, G Bradski Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2020 | 167 | 2020 |
| Image matching across wide baselines: From paper to practice Y Jin, D Mishkin, A Mishchuk, J Matas, P Fua, KM Yi, E Trulls International Journal of Computer Vision 129 (2), 517-547, 2021 | 164 | 2021 |
| Repeatability Is Not Enough: Learning Affine Regions via Discriminability D Mishkin, F Radenovic, J Matas European Conference on Computer Vision, 2018 | 164 | 2018 |
| MODS: Fast and Robust Method for Two-View Matching D Mishkin, J Matas, M Perdoch Computer Vision and Image Understanding 141, 81-93, 2015 | 159 | 2015 |
| Benchmarking Classic and Learned Navigation in Complex 3D Environments D Mishkin, A Dosovitskiy, V Koltun arXiv preprint arXiv:1901.10915, 2019 | 58 | 2019 |
| WxBS: Wide Baseline Stereo Generalizations D Mishkin, J Matas, M Perdoch, K Lenc British Machine Vision Conference, 2015, 12.1-12.12, 2015 | 54 | 2015 |
| Mobile visual commerce system J Romley, D Mishkin US Patent App. 15/011,160, 2016 | 32 | 2016 |
| Place Recognition with WxBS Retrieval D Mishkin, M Perdoch, J Matas CVPR 2015 Workshop on Visual Place Recognition in Changing Environments, 2015 | 28 | 2015 |
| In the Saddle: Chasing fast and repeatable features J Aldana-Iuit, D Mishkin, O Chum, J Matas Pattern Recognition (ICPR), 2016 23rd International Conference on, 675-680, 2016 | 24 | 2016 |
| Two-view matching with view synthesis revisited D Mishkin, M Perdoch, J Matas Image and Vision Computing New Zealand (IVCNZ), 2013 28th International …, 2013 | 20 | 2013 |
| Very Deep Residual Networks with MaxOut for Plant Identification in the Wild M Šulc, D Mishkin, J Matas Working Notes of CLEF 2016 - Conference and Labs of the Evaluation forum 1609, 2016 | 18 | 2016 |
| Efficient Initial Pose-graph Generation for Global SfM D Barath, D Mishkin, I Eichhardt, I Shipachev, J Matas Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 14 | 2021 |
| Leveraging Outdoor Webcams for Local Descriptor Learning M Pultar, D Mishkin, J Matas arXiv preprint arXiv:1901.09780, 2019 | 13 | 2019 |
| A Few Things One Should Know About Feature Extraction, Description and Matching K Lenc, J Matas, D Mishkin Computer Vision Winter Workshop 2014, 67--74, 2014 | 13* | 2014 |
| Models accuracy on imagenet 2012 val D Mishkin | 12 | 2017 |
| Saddle: Fast and repeatable features with good coverage J Aldana-Iuit, D Mishkin, O Chum, J Matas Image and Vision Computing 97, 3807, 2020 | 5 | 2020 |
Jiri MatasProfessor, Czech Technical UniversityVerified email at cmp.felk.cvut.cz
