Superpixel clustering with deep features for unsupervised road segmentation

11/16/2017
by   Shunta Saito, et al.
1

Vision-based autonomous driving requires classifying each pixel as corresponding to road or not, which can be addressed using semantic segmentation. Semantic segmentation works well when used with a fully supervised model, but in practice, the required work of creating pixel-wise annotations is very expensive. Although weakly supervised segmentation addresses this issue, most methods are not designed for road segmentation. In this paper, we propose a novel approach to road segmentation that eliminates manual annotation and effectively makes use of road-specific cues. Our method has better performance than other weakly supervised methods and achieves 98 the performance of a fully supervised method, showing the feasibility of road segmentation for autonomous driving without tedious and costly manual annotation.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset