We propose a new virtual image dataset called
“ParallelEye”. For that we present a dataset generation pipeline
that uses street map, computer graphics, virtual reality, and
rule modeling technologies to construct a realistic, large-scale
virtual urban traffic scene. The artificial scene matches the real
world well in terms of fidelity and geographic information. In
the artificial scene, we flexibly configure the camera (including
its position, height, and orientation) and the environmental
conditions, to collect diversified images. Each image has
been annotated automatically with ground truth including
semantic/instance segmentation, object bounding box, object
tracking, optical flow, and depth.
Website: http://openpv.cn/datasets/paralleleye
We propose a new virtual image dataset called
“ParallelEye-CS”. In computer graphics software, artificial scenes can flexibly
change environmental conditions and automatically generate
accurate and diverse ground-truth labels. Therefore, ParallelEye-CS has six labels and includes 20 tests that can be divided
into normal, environmental, and difficult tasks.
Website: http://openpv.cn/datasets/paralleleye-cs