datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
low-light-datasetLowlight-Smartphone-Dataset
[WACV'26] Low-light Smartphone Dataset (LSD)
This is the official dataset proposed in our paper titled "Illuminating Darkness: Learning to Enhance Low-light Images In-the-Wild"
📄 Paper: arXiv💻 Code: GitHub - LSD-TFFormer
Overview
We introduce LSD, the largest in-the-wild Single-Shot Low-Light Image Enhancement (SLLIE) dataset to date.
Dataset Structure
This repository contains the following training data files:
patch_DLL_gtPatch.tar.gz… See the full description on the dataset page: https://huggingface.co/datasets/ARM4588/Lowlight-Smartphone-Dataset.Low-light_Scene_Text_Dataset
Low-light Scene Text Dataset
This repository provides a low-light scene text recognition dataset for studying text recognition under challenging illumination conditions. The dataset is designed to support research on Low-light Scene Text Recognition (LLSTR), where text images may suffer from low contrast, noise, uneven illumination, blur, and other degradations commonly observed in nighttime or poorly lit environments.
The dataset contains two main parts:
LSTR: a large-scale… See the full description on the dataset page: https://huggingface.co/datasets/lumimusta/Low-light_Scene_Text_Dataset.low-light-dataset2Sintel-Low-light-Noise
Sintel Low-light Noise ELD
A synthetic low-light optical flow dataset derived from MPI Sintel using the ELD low-light noise preset.
This dataset contains noisy RGB frames for both the train and test splits and is intended for:
optical flow robustness evaluation in low-light conditions
fine-tuning pretrained optical flow models
controlled experiments on synthetic low-light degradation
Contents
The dataset contains ELD-corrupted Sintel frames for:
training
test… See the full description on the dataset page: https://huggingface.co/datasets/LForster/Sintel-Low-light-Noise.low_lightlow_light_rainy_datasetlow-light-project
Low-Light Restoration Dataset
Paired low-light / normal-light image patches for training and evaluation.
Contents of low-light.tar
low-light/
├── train/ 30,000 paired patches (60,000 files)
├── val/ 1,000 paired patches (2,000 files)
├── test/ 1,000 input patches (no ground truth)
└── dataset.py reference PyTorch Dataset (Python 3.10+)
All images are lossless WebP (.webp).
File naming
Every image is named… See the full description on the dataset page: https://huggingface.co/datasets/KBlueLeaf/low-light-project.Denoise_low_light