2020
DIRL: Domain-Invariant Representation Learning for Sim-to-Real Transfer
CoRL 2020
Generating large-scale synthetic data in simulation is a feasible alternative to collecting/labelling real data for training vision-based deep learning models, albeit the modelling inaccuracies do not generalize to the physical world. In this paper, we present a domain-invariant representation learn