Real-time HybridNets detects traffic object, drivable area, and road lane
Real-time HybridNets detects traffic object, drivable area, and road lane
HybridNets: End-to-End Perception Network
arXiv paper abstract https://arxiv.org/abs/2203.09035
arXiv PDF paper https://arxiv.org/ftp/arxiv/papers/2203/2203.09035.pdf
End-to-end Network has become increasingly important in multi-tasking. One ... example ... is ... perception system in autonomous driving.
... proposes several key optimizations to improve accuracy. First, ... proposes efficient segmentation head and box/class prediction networks based on weighted bidirectional feature network.
Second, ... proposes automatically customized anchor for each level in the weighted bidirectional feature network.
Third, ... proposes an efficient training loss function and training strategy to balance and optimize network.
... developed an end-to-end perception network to perform multi-tasking, including traffic object detection, drivable area segmentation and lane detection simultaneously, called HybridNets, which achieves better accuracy than prior art.
... can perform visual perception tasks in real-time and thus is a practical and accurate solution to the multi-tasking problem. ...
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