46 datasets found

Groups: Autonomous driving Organizations: No Organization

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  • DSEC: A Stereo Event Camera Dataset for Driving Scenarios

    A new dataset that contains demanding illumination conditions and provides a rich set of sensory data for autonomous driving.

  • Nuscenes

    Nuscenes is a large-scale autonomous driving dataset that provides high-resolution BEV semantic occupancy labels for roads and vehicles.

  • JPerceiver: Joint Perception Network for Depth, Pose and Layout Estimation in...

    Depth estimation, visual odometry, and bird’s-eye-view scene layout estimation present three critical tasks for driving scene perception, which is fundamental for motion...

  • NeRFs for Autonomous Driving

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

  • KITTI Raw

    Novel view synthesis is a long-standing problem that revolves around rendering frames of scenes from novel camera viewpoints.

  • WoodScape

    The WoodScape dataset consists of 10,000 annotated images captured from four different view angles: Front View (FV), Mirror-View Right (MVR), Mirror-View Left (MVL), and Rear...

  • Fishyscapes

    Fishyscapes: A benchmark for safe semantic segmentation in autonomous driving with annotations for pedestrian and vehicle detection.

  • MUAD: Multiple Uncertainties for Autonomous Driving

    MUAD: A synthetic dataset for autonomous driving with multiple uncertainties and annotations for semantic segmentation, depth estimation, object detection, and instance...

  • Real-world Vehicle Point Cloud

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

  • Argoverse2

    Argoverse2 is an open-source evolution of the original Argoverse

  • KITTI Benchmark

    A benchmark for stereo matching and depth estimation.

  • SceneFlow

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

  • NuScenes dataset

    The dataset used in the paper is the NuScenes dataset, which contains LiDAR point clouds and corresponding semantic annotations.

  • KITTI 2012

    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.

  • Argoverse

    The Argoverse dataset is a large-scale dataset for autonomous driving, containing 3D point clouds, semantic segmentation masks, and instance segmentation masks.

  • NEAT Dataset

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

  • CARLA

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

  • PandaSet

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

  • KITTI Vision Benchmark Suite

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

  • VoxelNet

    The VoxelNet dataset is a large-scale dataset for 3D object detection, consisting of 3D point clouds and corresponding annotations.