13 citations · 16 across the 2 of their papers we have counts for
6 papers
Real-Time Joint Semantic Segmentation and Depth Estimation Using Asymmetric Annotations
Vladimir Nekrasov, Thanuja Dharmasiri, Andrew Spek +3
Deployment of deep learning models in robotics as sensory information extractors can be a daunting task to handle, even using generic GPU cards. Here, we address three of its most…
CReaM: Condensed Real-time Models for Depth Prediction using Convolutional Neural Networks
Andrew Spek, Thanuja Dharmasiri, Tom Drummond
Since the resurgence of CNNs the robotic vision community has developed a range of algorithms that perform classification, semantic segmentation and structure prediction (depths, n…
ENG: End-to-end Neural Geometry for Robust Depth and Pose Estimation using CNNs
Thanuja Dharmasiri, Andrew Spek, Tom Drummond
Recovering structure and motion parameters given a image pair or a sequence of images is a well studied problem in computer vision. This is often achieved by employing Structure fr…
A Fast Method For Computing Principal Curvatures From Range Images
Andrew Spek, Wai Ho Li, Tom Drummond
Estimation of surface curvature from range data is important for a range of tasks in computer vision and robotics, object segmentation, object recognition and robotic grasping esti…
Joint Pose and Principal Curvature Refinement Using Quadrics
Andrew Spek, Tom Drummond
In this paper we present a novel joint approach for optimising surface curvature and pose alignment. We present two implementations of this joint optimisation strategy, including a…
Joint Prediction of Depths, Normals and Surface Curvature from RGB Images using CNNs
Thanuja Dharmasiri, Andrew Spek, Tom Drummond
Understanding the 3D structure of a scene is of vital importance, when it comes to developing fully autonomous robots. To this end, we present a novel deep learning based framework…