KITTI dataset and VOC2012 dataset

The KITTI dataset was jointly established by the Karlsruhe Institute of Technology (KIT) in Germany and the Toyota Technological Institute at Chicago (TTI-C) in the United States in 2012. It is currently one of the most commonly used datasets for evaluating computer vision algorithms in autonomous driving scenarios. This dataset is used to assess the performance of computer vision technologies such as stereo, optical flow, visual odometry, 3D object detection, and 3D tracking in vehicle-mounted environments. The KITTI dataset contains real image data collected from urban, rural, and highway scenes, with up to 15 vehicles and 30 pedestrians in each image, as well as various degrees of occlusion and truncation. For the 3D object detection task, the KITTI dataset provides 14,999 images along with corresponding point clouds, of which 7,481 groups are for training and 7,518 groups for testing. It is annotated for three types of objects in the scene: cars, pedestrians, and bicycles, totaling 80,256 labeled objects.