Shuda Li
Title
Cited by
Cited by
Year
Relocnet: Continuous metric learning relocalisation using neural nets
V Balntas, S Li, V Prisacariu
Proceedings of the European Conference on Computer Vision (ECCV), 751-767, 2018
922018
Recovering light directions and camera poses from a single sphere
KYK Wong, D Schnieders, S Li
European conference on computer vision, 631-642, 2008
502008
Flownet3d++: Geometric losses for deep scene flow estimation
Z Wang, S Li, H Howard-Jenkins, V Prisacariu, M Chen
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2020
252020
HDRFusion: HDR SLAM using a low-cost auto-exposure RGB-D sensor
S Li, A Handa, Y Zhang, A Calway
2016 Fourth International Conference on 3D Vision (3DV), 314-322, 2016
212016
RGBD relocalisation using pairwise geometry and concise key point sets
S Li, A Calway
2015 IEEE International Conference on Robotics and Automation (ICRA), 6374-6379, 2015
212015
Correspondence networks with adaptive neighbourhood consensus
S Li, K Han, TW Costain, H Howard-Jenkins, V Prisacariu
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
142020
Dual-resolution correspondence networks
X Li, K Han, S Li, V Prisacariu
Advances in Neural Information Processing Systems 33, 2020
112020
Absolute pose estimation using multiple forms of correspondences from RGB-D frames
S Li, A Calway
2016 IEEE International Conference on Robotics and Automation (ICRA), 4756-4761, 2016
72016
Thinking outside the box: generation of unconstrained 3D room layouts
H Howard-Jenkins, S Li, V Prisacariu
Asian Conference on Computer Vision, 432-448, 2018
62018
Resolution Correspondence Networks
G Tinchev, S Li, K Han, D Mitchell, R Kouskouridas
arXiv preprint arXiv:2012.09842, 2020
2020
Use of optic flow and visual direction in steering toward a target
S Li, DC Niehorster, L Li
Journal of Vision 10 (7), 799-799, 2010
2010
Using illumination estimated from silhouettes to carve surface details on visual hull
S Li, KKY Wong, D Schnieders
Proceedings of the British Machine Vision Conference, 2008
2008
Dual-Resolution Correspondence Networks–Supplementary Material–
X Li, K Han, S Li, V Prisacariu
threshold [px] 2 (4), 6, 0
FlowNet3D++: Geometric Losses For Deep Scene Flow Estimation (Supplementary Material)
Z Wang, S Li, H Howard-Jenkins, VA Prisacariu, M Chen
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Articles 1–14