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Datasets/IRV2V

IRV2V

IRregular V2V Dataset

ImagesLiDARIntroduced 2023-09-29

To facilitate research on asynchrony for collaborative perception, we simulate the first collaborative perception dataset with different temporal asynchronies based on CARLA, named IRregular V2V(IRV2V). We set 100ms as ideal sampling time interval and simulate various asynchronies in real-world scenarios from two main aspects: i) considering that agents are unsynchronized with the unified global clock, we uniformly sample a time shift δs∼U(−50,50)ms\delta_s\sim \mathcal{U}(-50,50)\text{ms}δs​∼U(−50,50)ms for each agent in the same scene, and ii) considering the trigger noise of the sensors, we uniformly sample a time turbulence δd∼U(−10,10)ms\delta_d\sim \mathcal{U}(-10,10)\text{ms}δd​∼U(−10,10)ms for each sampling timestamp. The final asynchronous time interval between adjacent timestamps is the summation of the time shift and time turbulence. In experiments, we also sample the frame intervals to achieve large-scale and diverse asynchrony. Each scene includes multiple collaborative agents ranging from 2 to 5. Each agent is equipped with 4 cameras with the resolution 600 ×\times× 800 and a 32-channel LiDAR. The detection range is 281.6m ×\times× 80m. It results in 34K images and 8.5K LiDAR sweeps. See more details in the Appendix.

Benchmarks

16k/AP5016k/AP702D Classification/AP502D Classification/AP702D Object Detection/AP502D Object Detection/AP703D/AP503D/AP703D Object Detection/AP503D Object Detection/AP70Object Detection/AP50Object Detection/AP70

Statistics

Papers
1
Benchmarks
12

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Tasks

16k2D Classification2D Object Detection3D3D Object DetectionObject Detection