ViSaRL: Saliency-Guided Visual Representations for Robot Learning
By Anthony Liang Teaching robots to perform complex control tasks from high-dimensional image inputs is a nontrivial problem. State-of-the-art methods require hundreds of manually collected expert demonstrations or hours to days of training in simulation to learn a simple pick-and-place skill. One reason for this is that images are cluttered with distractions for robots, such … Continue reading ViSaRL: Saliency-Guided Visual Representations for Robot Learning
