In nighttime driving scenes, due to insufficient and uneven lighting, and the scarcity of high-quality datasets, the miss rate of nighttime pedestrian detection (PD) is much higher than that of daytime. Vision-based distance detection (DD) has the advantages of low cost and good interpretability, but the existing methods have low precision, poor robustness, and the DD is mostly performed independently of PD.

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[1] Xiaobiao Dai, Yuxia Duan, "NIRPed", IEEE Dataport, 2022. [Online]. Available: http://dx.doi.org/10.21227/262q-dk26. Accessed: May. 27, 2024.
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doi = {10.21227/262q-dk26},
url = {http://dx.doi.org/10.21227/262q-dk26},
author = {Xiaobiao Dai; Yuxia Duan },
publisher = {IEEE Dataport},
title = {NIRPed},
year = {2022} }
TY - DATA
T1 - NIRPed
AU - Xiaobiao Dai; Yuxia Duan
PY - 2022
PB - IEEE Dataport
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Xiaobiao Dai, Yuxia Duan. (2022). NIRPed. IEEE Dataport. http://dx.doi.org/10.21227/262q-dk26
Xiaobiao Dai, Yuxia Duan, 2022. NIRPed. Available at: http://dx.doi.org/10.21227/262q-dk26.
Xiaobiao Dai, Yuxia Duan. (2022). "NIRPed." Web.
1. Xiaobiao Dai, Yuxia Duan. NIRPed [Internet]. IEEE Dataport; 2022. Available from : http://dx.doi.org/10.21227/262q-dk26
Xiaobiao Dai, Yuxia Duan. "NIRPed." doi: 10.21227/262q-dk26