Conditional Affordance Learning for Driving in Urban Environments

18 Jun 2018 Axel Sauer Nikolay Savinov Andreas Geiger

Most existing approaches to autonomous driving fall into one of two categories: modular pipelines, that build an extensive model of the environment, and imitation learning approaches, that map images directly to control outputs. A recently proposed third paradigm, direct perception, aims to combine the advantages of both by using a neural network to learn appropriate low-dimensional intermediate representations... (read more)

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