Popular Computer Vision Datasets for Autonomous Driving
KITTI
Dataset link: https://www.cvlibs.net/datasets/kitti/raw_data.php
KITTI is a dataset developed by Karlsruhe Institute of Technology and Toyota Technological Institute at Chicago for autonomous driving. It is basically a collection of images, LiDAR scans, and other sensor data collected from driving scenarios. It supports tasks like stereo vision, optical flow, visual odometry, 3D object detection, tracking, and depth estimation.
ApolloScape
Dataset link: https://apolloscape.auto/
ApolloScape is another open dataset proposed for the field of autonomous driving. It provides very dense images and point clouds along with dense labels for 2D and 3D object detection, lane markings segmentation, and scene understanding. The dataset ensembles multiple urban settings and weather conditions.
Dataset for Computer Vision
Computer Vision is an area in the field of Artificial Intelligence that enables machines to interpret and understand visual information. As in case of any other AI application, Computer vision also requires huge amount of data to give accurate results. These datasets provide all the necessary training material for these algorithms.
A dataset that will well-prepared and maintained will allow the model to learn from examples, recognize pattern and then make predictions about the unseen data. Therefore, the quality of datasets matters a lot, as it impacts the performance and robustness of computer vision applications.
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