Unsupervised Learning of Visual 3D Keypoints for Control
Boyuan Chen 1 Pieter Abbeel 1 Deepak Pathak 2
Abstract
Learning sensorimotor control policies from high-
dimensional images crucially relies on the quality
of the underlying visual representations. Prior
works show that structured latent space such as
visual keypoints often outperforms unstructured
representations for robotic control. However,
most of these representations, whet ...


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