31 citations · 35 across the 4 of their papers we have counts for
4 papers
Contrastive Language, Action, and State Pre-training for Robot Learning
Krishan Rana, Andrew Melnik, Niko Sünderhauf
In this paper, we introduce a method for unifying language, action, and state information in a shared embedding space to facilitate a range of downstream tasks in robot learning. O…
Addressing the Challenges of Open-World Object Detection
David Pershouse, Feras Dayoub, Dimity Miller +1
We address the challenging problem of open world object detection (OWOD), where object detectors must identify objects from known classes while also identifying and continually lea…
Zero-Shot Uncertainty-Aware Deployment of Simulation Trained Policies on Real-World Robots
Krishan Rana, Vibhavari Dasagi, Jesse Haviland +3
While deep reinforcement learning (RL) agents have demonstrated incredible potential in attaining dexterous behaviours for robotics, they tend to make errors when deployed in the r…
Deep Learning Features at Scale for Visual Place Recognition
Zetao Chen, Adam Jacobson, Niko Sunderhauf +5
The success of deep learning techniques in the computer vision domain has triggered a range of initial investigations into their utility for visual place recognition, all using gen…