Jack Valmadre
Jack Valmadre
Research scientist, Google Research
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
Fully-convolutional siamese networks for object tracking
L Bertinetto, J Valmadre, JF Henriques, A Vedaldi, PHS Torr
European conference on computer vision, 850-865, 2016
15012016
Staple: Complementary learners for real-time tracking
L Bertinetto, J Valmadre, S Golodetz, O Miksik, PHS Torr
Proceedings of the IEEE conference on computer vision and pattern …, 2016
10282016
End-to-end representation learning for correlation filter based tracking
J Valmadre, L Bertinetto, J Henriques, A Vedaldi, PHS Torr
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017
7502017
Learning feed-forward one-shot learners
L Bertinetto, JF Henriques, J Valmadre, PHS Torr, A Vedaldi
Advances in Neural Information Processing Systems, 523-531, 2016
2532016
Long-term tracking in the wild: A benchmark
J Valmadre, L Bertinetto, JF Henriques, R Tao, A Vedaldi, ...
Proceedings of the European Conference on Computer Vision (ECCV), 670-685, 2018
542018
General trajectory prior for non-rigid reconstruction
J Valmadre, S Lucey
Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on …, 2012
512012
Deterministic 3D human pose estimation using rigid structure
J Valmadre, S Lucey
Computer Vision–ECCV 2010, 467-480, 2010
482010
Dense semantic correspondence where every pixel is a classifier
H Bristow, J Valmadre, S Lucey
Proceedings of the IEEE International Conference on Computer Vision, 4024-4031, 2015
462015
Separable spatiotemporal priors for convex reconstruction of time-varying 3D point clouds
T Simon, J Valmadre, I Matthews, Y Sheikh
European Conference on Computer Vision, 204-219, 2014
312014
Efficient articulated trajectory reconstruction using dynamic programming and filters
J Valmadre, Y Zhu, S Sridharan, S Lucey
182012
Kronecker-Markov prior for dynamic 3D reconstruction
T Simon, J Valmadre, I Matthews, Y Sheikh
IEEE transactions on pattern analysis and machine intelligence 39 (11), 2201 …, 2016
112016
Learning detectors quickly with stationary statistics
J Valmadre, S Sridharan, S Lucey
Asian Conference on Computer Vision, 99-114, 2014
10*2014
Devon: Deformable volume network for learning optical flow
Y Lu, J Valmadre, H Wang, J Kannala, M Harandi, P Torr
The IEEE Winter Conference on Applications of Computer Vision, 2705-2713, 2020
82020
The importance of estimating object extent when tracking with correlation filters
L Bertinetto, J Valmadre, S Golodetz, O Miksik, PHS Torr
Report for the Visual Object Tracking Workshop, 2015
72015
Camera-less articulated trajectory reconstruction
Y Zhu, J Valmadre, S Lucey
6*
Closed-form solutions for low-rank non-rigid reconstruction
J Valmadre, S Sridharan, S Denman, C Fookes, S Lucey
2015 International Conference on Digital Image Computing: Techniques and …, 2015
32015
Home/Publications
S Dong, W Yuan, E Adelson, C Nagpal, K Miller, B Boecking, A Dubrawski, ...
Journal Article 26 (3), 388-395, 2017
2017
Stationary processes for object detection and non-rigid structure-from-motion
JL Valmadre
Queensland University of Technology, 2016
2016
Home/Publications
P Walker, S Nunnally, M Lewis, A Kolling, N Chakraborty, K Sycara, ...
Journal Article 31 (12), 1349-1376, 2012
2012
Graph rigidity for near-coplanar structure from motion
J Valmadre, B Upcroft, S Sridharan, S Lucey
Digital Image Computing Techniques and Applications (DICTA), 2011 …, 2011
2011
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Articles 1–20