Adversarial Appearance Learning in Augmented Cityscapes for Pedestrian Recognition in Autonomous Driving
Artem Savkin,Thomas Lapotre,Kevin Strauss,Uzair Akbar,Federico Tombari,Artem Savkin,Thomas Lapotre,Kevin Strauss,Uzair Akbar,Federico Tombari
In the autonomous driving area synthetic data is crucial for cover specific traffic scenarios which autonomous vehicle must handle. This data commonly introduces domain gap between synthetic and real domains. In this paper we deploy data augmentation to generate custom traffic scenarios with VRUs in order to improve pedestrian recognition. We provide a pipeline for augmentation of the Cityscapes d...
