Virtual KITTI Dataset

Virtual KITTI is a photo-realistic synthetic video dataset designed to learn and evaluate computer vision models for several video understanding tasks: object detection and multi-object tracking, scene-level and instance-level semantic segmentation, optical flow, and depth estimation. Virtual KITTI contains 21,260 images generated from five different virtual worlds in urban settings under different imaging and weather conditions. These photo-realistic synthetic images are automatically, exactly, and fully annotated for 2D and 3D multi-object tracking and at the pixel level with category, instance, flow, and depth labels.

虚拟KITTI是一个旨在学习与评估计算机视觉模型在多种视频理解任务中的性能的逼真合成视频数据集，包括目标检测与多目标跟踪、场景级与实例级语义分割、光流以及深度估计。该数据集由五个不同虚拟世界在都市环境下的不同成像和天气条件下生成的21,260张图像构成，这些图像具有高度逼真性。该数据集针对2D和3D多目标跟踪以及在像素级别对类别、实例、光流和深度标签进行了自动、精确且完整的标注。