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Using Synthetic Data for Improving Detection of Cyclists and Pedestrians in Autonomous Driving
 Kopčilová, Zuzana ; Musil, Petr (referee) ; Smrž, Pavel (advisor)
This thesis deals with creating a synthetic dataset for autonomous driving and the possibility of using it to improve the results of vulnerable traffic participants' detection. Existing works in this area either do not disclose the dataset creation process or are unsuitable for 3D object detection. Specific steps to create a synthetic dataset are proposed in this work, and the obtained samples are validated by visualization. In the experiments, the samples are then used to train the object detection model VoxelNet.
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