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Self-driving perception, LiDAR/camera fusion, trajectory prediction, drone perception, robot manipulation
2,023 datasets
Velodyne lidar sensors are widely used in autonomous vehicles and robotics. This dataset likely contains raw 3D point cloud data captured by such sensors. The data is hosted on Kaggle, but its specific collection details, size, and origin are unknown.
Kaggle hosts a dataset titled 'Drone Swarm Near-Miss Challenge'. The dataset likely contains data related to drone swarm operations and near-miss incidents. Its specific content, scale, and authorship are unknown.
kitti_mask is a dataset hosted on Kaggle. The title suggests it is derived from the KITTI Vision Benchmark Suite, a prominent resource for autonomous driving research. The dataset likely contains image data, potentially with segmentation masks, but specific details on size, format, and columns are unavailable.
Motion prediction data from Waymo, a leader in autonomous vehicle technology, published on Kaggle. The dataset likely contains sequences of object trajectories and sensor data for predicting the future motion of agents in a scene. Specific details on volume, format, and collection methodology require verification after download.
A dataset for drone delivery detection, published on Kaggle by IntRoLab. The dataset's specific content, scale, and collection details are not provided in the available metadata. Its platform tag suggests it may include audio data, but the exact data types and structure require verification after download.
A dataset titled 'data-story-slam' is available on Kaggle. The dataset's content likely contains narrative text data, as suggested by the title. No further details on size, origin, or specific content are provided in the available metadata.
VisDrone_Dataset is a collection of drone-captured images published on Kaggle. The dataset's specific scale, annotation details, and creation date are not provided in the available metadata. Its content and structure require verification after download.
A dataset of imagery captured by unmanned aerial vehicles (UAVs) in forested environments under sunny conditions. The dataset is hosted on Kaggle, but its specific size, collection dates, and authorship are unknown. Columns and sample data are unavailable, limiting detailed assessment.
UAV Forest Sunny - Part 1 (seq1-seq4) is a dataset of aerial imagery published on Kaggle. The title suggests it contains sequences of images captured by an unmanned aerial vehicle in a forest environment under sunny conditions. The dataset's specific content, scale, and collection details require verification after download.
A Kaggle-hosted dataset of aerial images intended for human detection tasks. The dataset likely contains images captured from drone platforms, focusing on identifying human figures from an overhead perspective. Specific details on volume, collection dates, and authorship are not provided in the available metadata.
SARD is a Search And Rescue Dataset containing images of humans taken by drones. The description indicates it is labeled with a single class. The dataset's author, organization, and update history are unknown.
DrivIng is a large-scale multimodal dataset for driving research, featuring full digital twin integration. It was authored by Dominik Rößle and published via Harvard Dataverse in January 2026.
VisDrone is a benchmark dataset for computer vision tasks using drone-captured imagery. The description indicates it supports object detection, object tracking, and crowd counting. The dataset's author, organization, and specific scale are not provided in the input.
VisDrone is a benchmark dataset for object detection and tracking tasks. It consists of drone-based aerial images, likely containing annotations for various objects. The dataset's author, organization, and specific scale are not provided in the input metadata.
nuScenes Mini is a subset of the full nuScenes dataset for autonomous vehicle perception. It contains annotated sensor data from a vehicle equipped with cameras, LIDAR, and radar. The dataset was created by Motional (formerly nuTonomy) for research in autonomous driving.
A Kaggle-hosted dataset likely containing images or video frames of drones, birds, balloons, and kites. The dataset's purpose is inferred to be training and evaluating computer vision models for detecting and classifying these aerial objects. Specific details on volume, source, and creation date are unavailable.
A collection of guava plant images published on Kaggle. The dataset likely contains visual data for agricultural analysis, though specific details on volume, collection method, and time range are not provided. Its content and structure require verification after download.
A dataset hosted on Kaggle, likely containing video sequences captured from unmanned aerial vehicles. The specific number of sequences, subjects, and collection details are not provided in the metadata. The dataset's primary purpose appears to be for developing and benchmarking computer vision algorithms.
A Kaggle dataset titled 'wardronestypes'. The dataset likely contains information about categories or classifications of autonomous military systems, such as drones. The author, organization, and specific details are unknown.
3-meter resolution Lidar Digital Elevation Models are the primary elevation data product distributed by the National Park Service. The dataset covers specific locations within the Great Smoky Mountains National Park, including Clingmans Dome, Cades Cove, and Bryson City.