134 citations · 197 across the 9 of their papers we have counts for
4 papers · 1 filter
What Would You Do? Acting by Learning to Predict
Adam Tow, Niko Sünderhauf, Sareh Shirazi +2
We propose to learn tasks directly from visual demonstrations by learning to predict the outcome of human and robot actions on an environment. We enable a robot to physically perfo…
Action Recognition: From Static Datasets to Moving Robots
Fahimeh Rezazadegan, Sareh Shirazi, Ben Upcroft +1
Deep learning models have achieved state-of-the- art performance in recognizing human activities, but often rely on utilizing background cues present in typical computer vision dat…
ARTiS: Appearance-based Action Recognition in Task Space for Real-Time Human-Robot Collaboration
Markus Eich, Sareh Shirazi, Gordon Wyeth
To have a robot actively supporting a human during a collaborative task, it is crucial that robots are able to identify the current action in order to predict the next one. Common…
On the Performance of ConvNet Features for Place Recognition
Niko Sünderhauf, Feras Dayoub, Sareh Shirazi +2
After the incredible success of deep learning in the computer vision domain, there has been much interest in applying Convolutional Network (ConvNet) features in robotic fields suc…