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Shuda Li
Shuda Li
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Titel
Zitiert von
Zitiert von
Jahr
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
1442018
Recovering light directions and camera poses from a single sphere
KYK Wong, D Schnieders, S Li
European conference on computer vision, 631-642, 2008
542008
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
532020
Dual-resolution correspondence networks
X Li, K Han, S Li, V Prisacariu
Advances in Neural Information Processing Systems 33, 17346-17357, 2020
402020
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
402020
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
262015
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
242016
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
152018
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
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
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