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Semantic Segmentation for Autonomous Driving: Model Evaluation, Dataset Generation, Perspective Comparison, and Real-Time Capability. (arXiv:2207.12939v1 [cs.CV])
cs.CV updates on arXiv.org arxiv.org
Environmental perception is an important aspect within the field of
autonomous vehicles that provides crucial information about the driving domain,
including but not limited to identifying clear driving areas and surrounding
obstacles. Semantic segmentation is a widely used perception method for
self-driving cars that associates each pixel of an image with a predefined
class. In this context, several segmentation models are evaluated regarding
accuracy and efficiency. Experimental results on the generated dataset confirm
that the segmentation model FasterSeg is fast …
arxiv autonomous autonomous driving comparison cv dataset dataset generation driving evaluation generation perspective real-time segmentation semantic time