Ravi Garg
TitleCited byYear
Unsupervised CNN for single view depth estimation: Geometry to the rescue
R Garg, VK BG, G Carneiro, I Reid
European Conference on Computer Vision, 740-756, 2016
4042016
Dense Variational Reconstruction of Non-Rigid Surfaces from Monocular Video
R Garg, A Roussos, A Lourdes
Computer Vision and Pattern Recognition (CVPR) 2013, 2013
1712013
A variational approach to video registration with subspace constraints
R Garg, A Roussos, L Agapito
International journal of computer vision 104 (3), 286-314, 2013
1052013
Unsupervised learning of monocular depth estimation and visual odometry with deep feature reconstruction
H Zhan, R Garg, C Saroj Weerasekera, K Li, H Agarwal, I Reid
Proceedings of the IEEE Conference on Computer Vision and Patterná…, 2018
852018
Dense Multibody Motion Estimation and Reconstruction from a Handheld Camera
A Roussos, C Russell, R Garg, L Agapito
ISMAR, 2012
382012
Robust trajectory-space tv-l1 optical flow for non-rigid sequences
R Garg, A Roussos, L Agapito
International Workshop on Energy Minimization Methods in Computer Vision andá…, 2011
312011
Dense multi-frame optic flow for non-rigid objects using subspace constraints
R Garg, L Pizarro, D Rueckert, L Agapito
Asian Conference on Computer Vision, 460-473, 2010
282010
Data-driven approximations to NP-hard problems
A Milan, SH Rezatofighi, R Garg, A Dick, I Reid
Thirty-First AAAI Conference on Artificial Intelligence, 2017
172017
Scaling CNNs for high resolution volumetric reconstruction from a single image
A Johnston, R Garg, G Carneiro, I Reid, A van den Hengel
Proceedings of the IEEE International Conference on Computer Vision, 939-948, 2017
102017
Just-in-Time Reconstruction: Inpainting Sparse Maps using Single View Depth Predictors as Priors
CS Weerasekera, T Dharmasiri, R Garg, T Drummond, I Reid
ICRA 2018, 2018
92018
Dense monocular reconstruction using surface normals
CS Weerasekera, Y Latif, R Garg, I Reid
2017 IEEE International Conference on Robotics and Automation (ICRA), 2524-2531, 2017
82017
Non-linear dimensionality regularizer for solving inverse problems
R Garg, A Eriksson, I Reid
arXiv preprint arXiv:1603.05015, 2016
82016
Learning Deeply Supervised Good Features to Match for Dense Monocular Reconstruction
CS Weerasekera, R Garg, Y Latif, I Reid
Asian Conference on Computer Vision, 609-624, 2018
5*2018
Addressing Challenging Place Recognition Tasks using Generative Adversarial Networks
Y Latif, R Garg, M Milford, I Reid
ICRA 2018, 2017
52017
Low-rank kernel subspace clustering
P Ji, I Reid, R Garg, H Li, M Salzmann
arXiv preprint arXiv:1707.04974 1, 2017
52017
Optimizable Object Reconstruction from a Single View
K Li, R Garg, M Cai, I Reid
arXiv preprint arXiv:1811.11921, 2018
12018
Dense Motion Capture of Deformable Surfaces from Monocular Video
R Garg
Queen Mary University of London, 2014
12014
Self-supervised Learning for Single View Depth and Surface Normal Estimation
H Zhan, CS Weerasekera, R Garg, I Reid
arXiv preprint arXiv:1903.00112, 2019
2019
Automatic estimation of the number of deformation modes in non-rigid SfM with missing data
C JuliÓ, M Paladini, R Garg, D Puig, L Agapito
Scandinavian Conference on Image Analysis, 381-392, 2011
2011
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Articles 1–19