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Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding
Alex Kendall, Vijay Badrinarayanan, Roberto Cipolla
We present a deep learning framework for probabilistic pixel-wise semantic segmentation, which we term Bayesian SegNet. Semantic segmentation is an important tool for visual scene…
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
Vijay Badrinarayanan, Alex Kendall, Roberto Cipolla
We present a novel and practical deep fully convolutional neural network architecture for semantic pixel-wise segmentation termed SegNet. This core trainable segmentation engine co…
Modelling Uncertainty in Deep Learning for Camera Relocalization
Alex Kendall, Roberto Cipolla
We present a robust and real-time monocular six degree of freedom visual relocalization system. We use a Bayesian convolutional neural network to regress the 6-DOF camera pose from…
PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization
Alex Kendall, Matthew Grimes, Roberto Cipolla
We present a robust and real-time monocular six degree of freedom relocalization system. Our system trains a convolutional neural network to regress the 6-DOF camera pose from a si…