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Invited Talk - "Object- and Action-Centric Representational Robot Learning"
Pete Florence · Daniel Seita

Fri Dec 11 09:46 AM -- 10:30 AM (PST) @

In this talk we'll discuss different views on representations for robot learning, in particular towards the goal of precise, generalizable vision-based manipulation skills that are sample-efficient and scalable to train. Object-centric representations, on the one hand, can enable using rich additional sources of learning, and can enable various efficient downstream behaviors. Action-centric representations, on the other hand, can learn high-level planning, and do not have to explicitly instantiate objectness. As case studies we’ll look at two recent papers in these two areas.

Author Information

Pete Florence (Robotics at Google)
Daniel Seita (University of California, Berkeley)

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