Learning to Steer by Mimicking Features from Heterogeneous Auxiliary Networks

7 Nov 2018Yuenan HouZheng MaChunxiao LiuChen Change Loy

The training of many existing end-to-end steering angle prediction models heavily relies on steering angles as the supervisory signal. Without learning from much richer contexts, these methods are susceptible to the presence of sharp road curves, challenging traffic conditions, strong shadows, and severe lighting changes... (read more)

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Evaluation Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK COMPARE
Steering Control BDD100k FM-Net Accuracy 85.03% # 1
Steering Control Comma.ai FM-Net MAE 0.7048 # 1
Steering Control Udacity FM-Net MAE 1.6236 # 1