The visual object tracking vot2013 challenge results M Kristan, R Pflugfelder, A Leonardis, J Matas, F Porikli, L Cehovin, ... Computer Vision Workshops (ICCVW), 2013 IEEE International Conference on, 98-111, 2013 | 2120 | 2013 |
Fixing the locally optimized RANSAC–Full experimental evaluation K Lebeda, J Matas, O Chum Research Report CTU–CMP–2012–17, Center for Machine Perception, Czech …, 2012 | 294 | 2012 |
Fixing the Locally Optimized RANSAC. K Lebeda, J Matas, O Chum BMVC, 1-11, 2012 | 294* | 2012 |
The thermal infrared visual object tracking VOT-TIR2016 challenge results M Felsberg, M Kristan, J Matas, A Leonardis, R Pflugfelder, G Häger, ... European Conference on Computer Vision, 824-849, 2016 | 171 | 2016 |
Long-term tracking through failure cases K Lebeda, S Hadfield, J Matas, R Bowden Proceedings of the IEEE International Conference on Computer Vision …, 2013 | 58 | 2013 |
Texture-Independent Long-Term Tracking Using Virtual Corners K Lebeda, S Hadfield, J Matas, R Bowden IEEE Transactions on Image Processing 25 (1), 359-371, 2016 | 29 | 2016 |
2D or not 2D: Bridging the gap between tracking and structure from motion K Lebeda, S Hadfield, R Bowden Computer Vision--ACCV 2014: 12th Asian Conference on Computer Vision …, 2015 | 24 | 2015 |
Natural action recognition using invariant 3D motion encoding S Hadfield, K Lebeda, R Bowden Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014 | 21 | 2014 |
HARD-PnP: PnP Optimization Using a Hybrid Approximate Representation S Hadfield, K Lebeda, R Bowden IEEE transactions on Pattern Analysis and Machine Intelligence, 2018 | 20 | 2018 |
The visual object tracking vot2015 challenge results K Matej, J Matas, A Leonardis, M Felsberg, L Čehovin, G Fernández, ... Workshop on the Visual Object Tracking Challenge (VOT, in conjunction with ICCV), 2015 | 20 | 2015 |
Hollywood 3D: What are the best 3D features for Action Recognition? S Hadfield, K Lebeda, R Bowden International Journal of Computer Vision 121 (1), 95-110, 2017 | 19 | 2017 |
Exploring Causal Relationships in Visual Object Tracking K Lebeda, S Hadfield, R Bowden Proceedings of the IEEE International Conference on Computer Vision, 3065-3073, 2015 | 16 | 2015 |
Tracking the untrackable: How to track when your object is featureless K Lebeda, J Matas, R Bowden Asian Conference on Computer Vision, 347-359, 2012 | 15 | 2012 |
Stereo reconstruction using top-down cues S Hadfield, K Lebeda, R Bowden Computer Vision and Image Understanding 157, 206-222, 2017 | 10 | 2017 |
TMAGIC: A model-free 3D tracker K Lebeda, S Hadfield, R Bowden IEEE Transactions on Image Processing 26 (9), 4378-4388, 2017 | 5 | 2017 |
Dense Rigid Reconstruction from Unstructured Discontinuous Video K Lebeda, S Hadfield, R Bowden Proceedings of the IEEE International Conference on Computer Vision …, 2015 | 5 | 2015 |
Direct-from-Video: Unsupervised NRSfM K Lebeda, S Hadfield, R Bowden Computer Vision–ECCV 2016 Workshops, 578-594, 2016 | 3 | 2016 |
Robust Sampling Consensus K Lebeda České vysoké učení technické v Praze. Vypočetní a informační centrum., 2013 | 2 | 2013 |
The visual object tracking VOT2016 challenge results SJ Hadfield, R Bowden, K Lebeda Lecture Notes in Computer Science 9914, 777-823, 2016 | | 2016 |
2D and 3D tracking and modelling. K Lebeda University of Surrey, 2016 | | 2016 |