Spring 2017

Supersizing Self-Supervision: Learning Perception and Action without Human Supervision

Tuesday, Mar. 28, 2017 2:15 pm2:55 pm PDT

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In this talk, I will discuss how to learn representation for perception and action without using any manual supervision. First, I am going to discuss how we can learn ConvNets for vision in a completely unsupervised manner using auxiliary tasks. Specifically, I am going to demonstrate how spatial context in images and viewpoint changes in videos can be used to train visual representations. Next, I am going to talk about how we can use a robot to physically explore the world and learn visual representations for classification/recognition tasks. Finally, I am going to talk about how we can perform end-to-end learning for actions using self-supervision.