LoLI-Street (Low-Light Images of Streets)

We introduce low-light image enhancement benchmark dataset “Low-light Images of Streets (LoLI-Street),” which contains three subsets: train, validation, and test. The train and validation sets consist of 30k and 3k paired low-light and high-light images, respectively, and the real low-light test set (RLLT) contains 1k images under real-world low-light conditions, totaling 33k images.

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Citation:

If you use the dataset, please cite our paper:

@InProceedings{Islam_2024_ACCV,
    author    = {Islam, Md Tanvir and Alam, Inzamamul and Woo, Simon S. and Anwar, Saeed and Lee, IK Hyun and Muhammad, Khan},
    title     = {LoLI-Street: Benchmarking Low-light Image Enhancement and Beyond},
    booktitle = {Proceedings of the Asian Conference on Computer Vision (ACCV)},
    month     = {December},
    year      = {2024},
    pages     = {1250-1267}}

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