Learning Accurate and Human-Like Driving using Semantic Maps and Attention
Simon Hecker,Dengxin Dai,Alexander Liniger,Martin Hahner,Luc Van Gool,Simon Hecker,Dengxin Dai,Alexander Liniger,Martin Hahner,Luc Van Gool
This paper investigates how end-to-end driving models can be improved to drive more accurately and human-like. To tackle the first issue we exploit semantic and visual maps from HERE Technologies and augment the existing Drive360 dataset with such. The maps are used in an attention mechanism that promotes segmentation confidence masks, thus focusing the network on semantic classes in the image tha...
