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Self-driving perception, LiDAR/camera fusion, trajectory prediction, drone perception, robot manipulation
2,016 datasets
Financial information reported by entities in Colombia's solidarity sector, supervised by the Superintendencia de la Economía Solidaria. The dataset covers reports from 2017 to the present, published by datos.gov.co.
USEFUL provides 10 synchronized sensor streams, including LiDAR, radar, RGB, thermal, SWIR, and polarimetric cameras, for autonomous vehicle perception research. It is specifically designed to advance perception in challenging conditions like night, glare, fog, and rain. The dataset includes accurate 3D and 2D bounding box annotations paired with GPS/INS ego-pose data.
A tabular dataset comparing a specific UAV navigation approach with recent studies. The 9.5 KB Excel file was authored by Gobinda Chandra Sarker and last updated on April 3, 2026. The platform tags suggest the data relates to obstacle avoidance and depth estimation for autonomous flight.
Francesc Serradó's dataset contains field, drone, and satellite data used to study how prescribed burns can trigger Diplodia shoot blight in pine forests. The dataset is a single XLSX file sized at 107.5 KB. It was last updated on April 3, 2026.
KITTI360-mini-RGB is a subset of the KITTI-360 dataset, likely containing street-level RGB images. The dataset is published on Kaggle, but specific details about its size, collection dates, and creators are not provided in the available metadata. Its content and scale require verification after download.
A dataset titled 'MH-SoyaHealthVision-NonUAV' is hosted on Kaggle. The title suggests it contains imagery related to soybean crop health, likely captured from non-UAV (Unmanned Aerial Vehicle) platforms. No further metadata is available to confirm its size, origin, or specific content.
DRONE_VIDEOS_02 is a dataset of video files captured by drones, published on the Kaggle platform. The dataset's specific content, scale, and collection details are not described in the available metadata. Further details such as the number of videos, their resolution, duration, and annotation status require verification after download.
Disparity data from the Robotic Arm Camera on NASA's Phoenix Mars Lander. The dataset contains processed imaging operations data from the RAC instrument. It originates from the National Aeronautics and Space Administration and was last updated in March 2026.
KITTI_lidar_seq3 is a dataset from the KITTI Vision Benchmark Suite, likely containing a sequence of lidar point cloud scans. The data is hosted on Kaggle and is associated with platform tags for computer vision and autonomous driving. Specific details on the number of frames, collection method, and exact content require verification after download.
A sequence of lidar point cloud data from the KITTI benchmark platform. The dataset is published on Kaggle and is associated with autonomous driving research. Specific details on collection date, sequence length, and data volume are not provided in the available metadata.
KITTI_lidar_seq5 is a dataset from the KITTI Vision Benchmark Suite, likely containing a sequence of LiDAR sensor data. The dataset is hosted on Kaggle, but detailed metadata such as column descriptions, sample data, and size are unavailable. Its origin and last update date are unknown.
KITTI_lidar_seq4 is a dataset from the Kaggle platform. The title suggests it contains LiDAR sensor data, likely from the KITTI autonomous driving research suite. The specific content, scale, and collection details are not provided in the available metadata.
KITTI_lidar_seq7 is a dataset hosted on Kaggle. The title suggests it contains a sequence of lidar sensor data, likely related to the KITTI Vision Benchmark Suite for autonomous driving research. The dataset's specific content, size, and collection details are not provided in the available metadata.
KITTI_lidar_seq6 is a dataset from the KITTI Vision Benchmark Suite, likely containing sensor data for autonomous driving research. The data appears to be a specific sequence (sequence 6) of lidar point cloud scans, commonly used for tasks like 3D object detection and tracking. It is hosted on Kaggle, but detailed metadata such as the number of frames, collection specifics, and author information are not provided.
A dataset concerning unmanned aerial vehicle (UAV) signals, hosted on Kaggle. The dataset's specific content, size, and collection details are not provided in the available metadata. Its platform tags suggest it likely contains tabular telemetry or signal processing data related to drone operations.
KITTI_lidar_seq9 is a dataset likely containing a sequence of lidar point cloud scans. The data originates from the KITTI Vision Benchmark Suite, a standard resource for autonomous driving research. It is hosted on Kaggle, but specific details on collection date, sequence length, and annotation are not provided in the metadata.
KITTI_lidar_seq10 is a sequence of LiDAR sensor data, likely from the KITTI Vision Benchmark Suite. The dataset is hosted on Kaggle, but its specific contents, size, and collection details are not provided in the metadata. Its title suggests it contains raw or processed 3D point cloud scans, a common data type for robotics and self-driving car research.
KITTI_rgb_seq67 is a dataset of RGB image sequences published on Kaggle. The title and platform tags suggest it is part of the KITTI benchmark suite, likely containing video frames for computer vision tasks. Specific details on the number of images, collection method, and author are unavailable from the provided metadata.
KITTI_rgb_seq59 is a dataset of RGB image sequences from the KITTI platform, likely related to autonomous driving research. The dataset is hosted on Kaggle, but specific details about its size, collection method, and creation date are not provided. Columns and sample data are unknown, limiting immediate assessment of its structure and content.
KITTI_rgb_seq034 is a sequence of RGB images from the KITTI Vision Benchmark Suite, a standard dataset for autonomous driving research. The sequence likely contains consecutive frames captured from a vehicle-mounted camera, suitable for tasks like visual odometry or object tracking. This dataset is published on Kaggle, but its specific details, such as the number of frames and collection context, require verification after download.