HybridNets: End-to-End Perception Network

Understand

End-to-end Network has become increasingly important in multi-tasking.

• One prominent example of this is the growing significance of a driving perception system in autonomous driving.
• This paper systematically studies an end-to-end perception network for multi-tasking and proposes several key optimizations to improve accuracy.
• First, the paper proposes efficient segmentation head and box/class prediction networks based on weighted bidirectional feature network.