280 citations · 298 across the 2 of their papers we have counts for
3 papers
cs.CV2017
Geometric Loss Functions for Camera Pose Regression with Deep Learning
Alex Kendall, Roberto Cipolla
Deep learning has shown to be effective for robust and real-time monocular image relocalisation. In particular, PoseNet is a deep convolutional neural network which learns to regre…
stat.ML2017★ 18 cited
Concrete Dropout
Yarin Gal, Jiri Hron, Alex Kendall
Dropout is used as a practical tool to obtain uncertainty estimates in large vision models and reinforcement learning (RL) tasks. But to obtain well-calibrated uncertainty estimate…
cs.CV2017★ 280 cited
End-to-End Learning of Geometry and Context for Deep Stereo Regression
Alex Kendall, Hayk Martirosyan, Saumitro Dasgupta +4
We propose a novel deep learning architecture for regressing disparity from a rectified pair of stereo images. We leverage knowledge of the problem's geometry to form a cost volume…