224 citations · 708 across the 24 of their papers we have counts for
Showing 2017Show all
3 papers · 1 filter
cs.AI2017
Learning from lions: inferring the utility of agents from their trajectories
Adam D. Cobb, Andrew Markham, Stephen J. Roberts
We build a model using Gaussian processes to infer a spatio-temporal vector field from observed agent trajectories. Significant landmarks or influence points in agent surroundings…
cs.CV2017★ 27 cited
3D Object Reconstruction from a Single Depth View with Adversarial Learning
Bo Yang, Hongkai Wen, Sen Wang +3
In this paper, we propose a novel 3D-RecGAN approach, which reconstructs the complete 3D structure of a given object from a single arbitrary depth view using generative adversarial…
cs.RO2017★ 136 cited
Towards Monocular Vision based Obstacle Avoidance through Deep Reinforcement Learning
Linhai Xie, Sen Wang, Andrew Markham +1
Obstacle avoidance is a fundamental requirement for autonomous robots which operate in, and interact with, the real world. When perception is limited to monocular vision avoiding c…