most citedJoint Prediction of Depths, Normals and Surface Curvature from RGB Images using CNNs

13 citations · 17 across the 4 of their papers we have counts for

collaborators

5 papers

cs.RO20191 cited

Embracing Contact: Pushing Multiple Objects with Robot's Forearm

Akansel Cosgun, Luke Ditria, Shayne D'Lima +1

Grasping is the dominant approach for robot manipulation, but only a single object can be grasped at a time. Nonprehensile manipulation offers richer set of interactions, however s…

cs.RO2019

Practical Robot Learning from Demonstrations using Deep End-to-End Training

Akansel Cosgun, Thomas Rowntree, Ian Reid +1

Robots need to learn behaviors in intuitive and practical ways for widespread deployment in human environments. To learn a robot behavior end-to-end, we train a variant of the ResN…

cs.CV20173 cited

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…

cs.CV2017

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…

cs.CV201713 cited

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…