Abstract: Imitation Learning (IL) is a promising paradigm for learning dynamic manipulation of deformable objects since it does not depend on difficult-to-create accurate simulations of such objects.

TL;DR: We show how object detection models can be turned into multi-object tracking models with almost no overhead. We also introduce a pre-training scheme on detection that improves tracking without ...