RAdar Dataset In Adverse weaThEr
RADIATE (RAdar Dataset In Adverse weaThEr) is new automotive dataset created by Heriot-Watt University which includes Radar, Lidar, Stereo Camera and GPS/IMU.
The data is collected in different weather scenarios (sunny, overcast, night, fog, rain and snow) to help the research community to develop new methods of vehicle perception.
The radar images are annotated in 7 different scenarios: Sunny (Parked), Sunny/Overcast (Urban), Overcast (Motorway), Night (Motorway), Rain (Suburban), Fog (Suburban) and Snow (Suburban). The dataset contains 8 different types of objects (car, van, truck, bus, motorbike, bicycle, pedestrian and group of pedestrians).
Source: https://github.com/marcelsheeny/radiate_sdk
Image Source: https://github.com/marcelsheeny/radiate_sdk
Variants: RADIATE
This dataset is used in 2 benchmarks:
| Task | Model | Paper | Date |
|---|---|---|---|
| Multiple Object Tracking | SIRA | SIRA: Scalable Inter-frame Relation and … | 2024-11-04 |
| 2D Object Detection | SIRA | SIRA: Scalable Inter-frame Relation and … | 2024-11-04 |
| Multiple Object Tracking | TempoRadar | Exploiting Temporal Relations on Radar … | 2022-04-03 |
| 2D Object Detection | TempoRadar | Exploiting Temporal Relations on Radar … | 2022-04-03 |
Recent papers with results on this dataset: