  Vanishing points (VPs) play a vital role in various computer vision tasks,
especially for recognizing the 3D scenes from an image. In the real-world
scenario of automobile applications, it is costly to manually obtain the
external camera parameters when the camera is attached to the vehicle or the
attachment is accidentally perturbed. In this paper we introduce a simple but
effective end-to-end vanishing point detection. By automatically calculating
intersection of the extrapolated lane marker annotations, we obtain
geometrically consistent VP labels and mitigate human annotation errors caused
by manual VP labeling. With the calculated VP labels we train end-to-end VP
Detector via heatmap estimation. The VP Detector realizes higher accuracy than
the methods utilizing manual annotation or lane detection, paving the way for
accurate online camera calibration.
