{"url":"/dataset/loli-street","name":"LoLI-Street","full_name":"Low-Light Images of Streets","description_markdown":"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.\r\n\r\n1. [Download LoLI-Street Dataset]( https://www.kaggle.com/datasets/tanvirnwu/loli-street-low-light-image-enhancement-of-street)\r\n2. [Read Full Paper](https://openaccess.thecvf.com/content/ACCV2024/html/Islam_LoLI-Street_Benchmarking_Low-light_Image_Enhancement_and_Beyond_ACCV_2024_paper.html)\r\n\r\n## Citation:\r\nIf you use the dataset, please cite our paper:\r\n\r\n```python\r\n@InProceedings{Islam_2024_ACCV,\r\n    author    = {Islam, Md Tanvir and Alam, Inzamamul and Woo, Simon S. and Anwar, Saeed and Lee, IK Hyun and Muhammad, Khan},\r\n    title     = {LoLI-Street: Benchmarking Low-light Image Enhancement and Beyond},\r\n    booktitle = {Proceedings of the Asian Conference on Computer Vision (ACCV)},\r\n    month     = {December},\r\n    year      = {2024},\r\n    pages     = {1250-1267}}\r\n```\r\n\r\nThank you!","description_withheld":null,"homepage":"https://github.com/tanvirnwu/TriFuse","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":{"name":"Attribution-NonCommercial 4.0 International","url":"https://www.kaggle.com/datasets/tanvirnwu/loli-street-low-light-image-enhancement-of-street"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Image Enhancement","url":"/task/image-enhancement","datasets_with_task":"/datasets/task/image-enhancement"},{"name":"Low-Light Image Enhancement","url":"/task/low-light-image-enhancement","datasets_with_task":"/datasets/task/low-light-image-enhancement"},{"name":"Autonomous Driving","url":"/task/autonomous-driving","datasets_with_task":"/datasets/task/autonomous-driving"},{"name":"Low-light Image Deblurring and Enhancement","url":"/task/low-light-image-deblurring-and-enhancement","datasets_with_task":"/datasets/task/low-light-image-deblurring-and-enhancement"},{"name":"Low-light Pedestrian Detection","url":"/task/low-light-pedestrian-detection","datasets_with_task":"/datasets/task/low-light-pedestrian-detection"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["LoLI-Street"],"data_loaders":[],"num_papers_in_archive":0,"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."}