Jack Valmadre
Jack Valmadre
Research scientist, Google Research
google.com üzerinde doğrulanmış e-posta adresine sahip - Ana Sayfa
Alıntı yapanlar
Alıntı yapanlar
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
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
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
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
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
General trajectory prior for non-rigid reconstruction
J Valmadre, S Lucey
Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on …, 2012
Deterministic 3D human pose estimation using rigid structure
J Valmadre, S Lucey
Computer Vision–ECCV 2010, 467-480, 2010
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
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
Measuring performance in real time during remote human-robot operations with adjustable autonomy
D Schreckenghost, T Milam, T Fong
IEEE Intelligent Systems, 36-45, 2010
Efficient articulated trajectory reconstruction using dynamic programming and filters
J Valmadre, Y Zhu, S Sridharan, S Lucey
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
Learning detectors quickly with stationary statistics
J Valmadre, S Sridharan, S Lucey
Asian Conference on Computer Vision, 99-114, 2014
Shape-constrained whole-body adaptivity
M Travers, C Gong, H Choset
2015 IEEE International Symposium on Safety, Security, and Rescue Robotics …, 2015
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
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
Camera-less articulated trajectory reconstruction
Y Zhu, J Valmadre, S Lucey
Advertiser-Specific Minimum Bids and Advertising Budgets in Keyword Search Auctions
P Desai, W Shin
Working Paper, Duke University, 2009
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
Stationary processes for object detection and non-rigid structure-from-motion
JL Valmadre
Queensland University of Technology, 2016
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Makaleler 1–20