15 datasets found

The dataset used for training and evaluation of the proposed framework for unsupervised metric relocalization.

The Argoverse dataset is a large dataset of real-world outdoor driving scenes.

The KITTI benchmark dataset is used to evaluate the performance of the proposed method. The dataset contains large-scale outdoor sequences of images captured by a forward-facing...

Scalability in perception for autonomous driving: Waymo open dataset.

The KITTI-360 dataset is an extension of the KITTI dataset, containing 10 new sequences recorded in 2013, with a focus on 360-degree views.

The dataset used in the paper is a large-scale dataset for autonomous driving and UAV racing, generated using the Sim4CV simulator.

Neural Radiance Fields (NeRFs) have emerged as promising tools for advancing autonomous driving (AD) research, offering scalable closed-loop simulation and data augmentation...

The dataset used in this paper is a real-world vehicle point cloud collected from a real vehicle self-driving process.

Large dataset for stereo matching, optical flow, and scene flow estimation

KITTI 2012 is a real-world dataset in the outdoor scenario, and contains 194 training and 195 testing stereo image pairs with the size of 376 × 1240.

The NEAT dataset, used for training and evaluation of the Neural Attention Fields (NEAT) model.

The CARLA dataset is a complex urban-like environment with multi-agent dynamics, pedestrians, intersections, cross-traffic, roundabout, and changing weather conditions.

A multi-modal dataset capturing self-driving scenes in various conditions, including different times of day and weather.

The KITTI Vision Benchmark Suite is a dataset used for object detection and tracking in autonomous vehicles.

The dataset used in the paper is the KITTI dataset, which is a benchmark for monocular depth estimation. The dataset consists of a large collection of images and corresponding...