{"url":"/dataset/durlar","name":"DurLAR","full_name":"A High-Fidelity 128-Channel LiDAR Dataset with Panoramic Ambient and Reflectivity Imagery","description_markdown":"DurLAR is a high-fidelity 128-channel 3D LiDAR dataset with panoramic ambient (near infrared) and reflectivity imagery for multi-modal autonomous driving applications. Compared to existing autonomous driving task datasets, DurLAR has the following novel features:  \r\n\r\n-  High vertical resolution **LiDAR** with **128 channels**, which is twice that of any existing datasets, full **360 degree depth**, range accuracy to ±2 cm at 20-50m.  \r\n- **Ambient illumination (near infrared)** and **reflectivity panoramic imagery** are made available in the Mono16 format (2048 × 128 resolution), with this being only dataset to make this provision.  \r\n- No rolling shutter effect, as our flash LiDAR captures all 128 channels simultaneously.  \r\n- **Ambient illumination data** is recorded via an on-board lux meter, which is again not available in previous datasets.  \r\n- High-fidelity **GNSS/INS** available via an onboard OxTS navigation unit operating at 100 Hz and receiving position and timing data from multiple GNSS con-stellations in addition to GPS.  \r\n- KITTI data format adopted as the de facto dataset format such that it can be parsed using both the DurLAR development kit and existing KITTI-compatible tools.   \r\n- **Diversity over repeated locations** such that the dataset has been collected under diverse environmental and weather conditions over the same driving route with additional variations in the time of day relative to environmental conditions.\r\n\r\n## Sensor placement\r\n\r\n- **LiDAR**: [Ouster OS1-128 LiDAR sensor](https://ouster.com/products/os1-lidar-sensor/) with 128 channels vertical resolution\r\n\r\n- **Stereo** Camera: [Carnegie Robotics MultiSense S21 stereo camera](https://carnegierobotics.com/products/multisense-s21/) with grayscale, colour, and IR enhanced imagers, 2048x1088 @ 2MP resolution\r\n\r\n- **GNSS/INS**: [OxTS RT3000v3](https://www.oxts.com/products/rt3000-v3/) global navigation satellite and inertial navigation system, supporting localization from GPS, GLONASS, BeiDou, Galileo, PPP and SBAS constellations\r\n\r\n- **Lux Meter**: [Yocto Light V3](http://www.yoctopuce.com/EN/products/usb-environmental-sensors/yocto-light-v3), a USB ambient light sensor (lux meter), measuring ambient light up to 100,000 lux","description_withheld":null,"homepage":"https://github.com/l1997i/DurLAR","introduced_date":"2021-12-01","introduced_date_note":null,"introduced_by":null,"license":{"name":"CC","url":"https://collections.durham.ac.uk/collections/r2gq67jr192"},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"3D","url":"/datasets/modality/3d"},{"name":"Point cloud","url":"/datasets/modality/point-cloud"},{"name":"Time series","url":"/datasets/modality/time-series"},{"name":"Stereo","url":"/datasets/modality/stereo"},{"name":"RGB Video","url":"/datasets/modality/rgb-video"},{"name":"LiDAR","url":"/datasets/modality/lidar"}],"tasks":[{"name":"Depth Estimation","url":"/task/depth-estimation","datasets_with_task":"/datasets/task/depth-estimation"},{"name":"Autonomous Driving","url":"/task/autonomous-driving","datasets_with_task":"/datasets/task/autonomous-driving"},{"name":"3D Depth Estimation","url":"/task/3d-depth-estimation","datasets_with_task":"/datasets/task/3d-depth-estimation"}],"languages":[{"name":"English","url":"/datasets/language/english"},{"name":"Chinese","url":"/datasets/language/chinese"}],"variants":["DurLAR"],"data_loaders":[],"num_papers_in_archive":5,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}