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Low-Light Image Enhancement datasets
archive 2025-07-2823 datasets carry the task tag "Low-Light Image Enhancement" (the task itself: Low-Light Image Enhancement), ordered by the archive's paper count. Page 1 of 1: 23 shown of 23. Facet routes are this site's own (the archive records the tag string, not a page).
The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.
Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets
All 12,172
Question Answering 413Semantic Segmentation 347Object Detection 332Image Classification 283Classification 222Text Classification 167Language Modelling 166Text Generation 162Visual Question Answering (VQA) 144Named Entity Recognition (NER) 130Pose Estimation 124Anomaly Detection 119Action Recognition 115Instance Segmentation 111Sentiment Analysis 104Text Summarization 98Domain Adaptation 96Speech Recognition 96Reading Comprehension 95Information Retrieval 932D Object Detection 92Image Retrieval 87Machine Translation 82Relation Extraction 822D Semantic Segmentation 81Natural Language Inference 81Image Captioning 79Image Generation 79Depth Estimation 77Node Classification 75Natural Language Understanding 72Autonomous Driving 70Code Generation 70Object Tracking 693D Object Detection 67Face Recognition 67Link Prediction 67Person Re-Identification 65Data Augmentation 63Multi-Task Learning 593D Reconstruction 58Common Sense Reasoning 56Recommendation Systems 56Video Understanding 56Optical Character Recognition (OCR) 55Graph Classification 54Abstractive Text Summarization 52Emotion Recognition 52Medical Image Segmentation 52Word Embeddings 52Low-Light Image Enhancement 23
Low-Light Image Enhancement datasets 1–23 of 23
LOL (LOw-Light dataset)
The LOL dataset is composed of 500 low-light and normal-light image pairs and divided into 485 training pairs and 15 testing pairs.
257 papers · 2 benchmarks
The 3DMATCH benchmark evaluates how well descriptors (both 2D and 3D) can establish correspondences between RGB-D frames of different views.
175 papers · 3 benchmarks
SID (See-in-the-Dark)
The See-in-the-Dark (SID) dataset contains 5094 raw short-exposure images, each with a corresponding long-exposure reference image.
155 papers · 3 benchmarks
AFLW (Annotated Facial Landmarks in the Wild)
The Annotated Facial Landmarks in the Wild (AFLW) is a large-scale collection of annotated face images gathered from Flickr, exhibiting a large variety in appearance (e.g., pose, expression, ethnicity, age, gender) as well as general…
154 papers · 11 benchmarks
LLVIP (A Visible-infrared Paired Dataset for Low-light Vision)
Visible-infrared Paired Dataset for Low-light Vision 30976 images (15488 pairs) 24 dark scenes, 2 daytime scenes Support for image-to-image translation (visible to infrared, or infrared to visible), visible and infrared image fusion,…
116 papers · 6 benchmarks
DICM is a dataset for low-light enhancement which consists of 69 images collected with commercial digital cameras.
86 papers · 1 benchmark
ExDark (Exclusively Dark Image Dataset)
The Exclusively Dark (ExDARK) dataset is a collection of 7,363 low-light images from very low-light environments to twilight (i.e 10 different conditions) with 12 object classes (similar to PASCAL VOC) annotated on both image class level…
58 papers · 2 benchmarks
The MIT-Adobe FiveK dataset consists of 5,000 photographs taken with SLR cameras by a set of different photographers.
28 papers · 4 benchmarks
LOL-v2 (LOL-v2-real)
LOL-v2-real contains 689 low-/normal-light image pairs for training and 100 pairs for testing.
24 papers · 1 benchmark
SMID (Seeing motion in the dark)
This is the low-light image enhancement dataset collected by the CVPR 2018 paper "Seeing Motion in the Dark".
21 papers · 1 benchmark
The real captured dataset of LOL contains 500 low/normallight image pairs.
13 papers · 1 benchmark
LOL-v2-synthetic (From Fidelity to Perceptual Quality: A Semi-Supervised Approach for Low-Light Image Enhancement)
From Fidelity to Perceptual Quality: A Semi-Supervised Approach for Low-Light Image Enhancement
11 papers · 1 benchmark
To make synthetic images match the property of real dark photography, we analyze the illumination distribution of low-light images.
9 papers · 1 benchmark
MEF (Multi-exposure image fusion)
Multi-exposure image fusion (MEF) is considered an effective quality enhancement technique widely adopted in consumer electronics, but little work has been dedicated to the perceptual quality assessment of multi-exposure fused images.
9 papers · 1 benchmark
LoLi-Phone is a large-scale low-light image and video dataset for Low-light image enhancement (LLIE).
5 papers · 0 benchmarks
SDSD-indoor (Seeing Dynamic Scene in the Dark: High-Quality Video Dataset with Mechatronic Alignment)
The dataset collected by the paper Seeing Dynamic Scene in the Dark: High-Quality Video Dataset with Mechatronic Alignment, ICCV 2021
5 papers · 1 benchmark
SDSD-outdoor (Seeing Dynamic Scene in the Dark: High-Quality Video Dataset with Mechatronic Alignment)
Seeing Dynamic Scene in the Dark: High-Quality Video Dataset with Mechatronic Alignment
4 papers · 1 benchmark
Sony-Total-Dark (SID Sony subset without gamma correction)
Original SID dataset is introduced in "Learning to See in the Dark".
3 papers · 1 benchmark
Canon RAW Low Light (Canon Camera Low Light RAW Image Dataset)
The goal of this project is to present two new datasets that seek to expand the capability of the Learning to See in the Dark Low-light enhancement CNN for the Canon 6D DSLR, and explore how the network performs when modified in various…
1 paper · 2 benchmarks
LLNeRF Dataset is a real-world dataset as a benchmark for model learning and evaluation.
1 paper · 0 benchmarks
Nikon RAW Low Light (Nikon Camera Low Light RAW Image Dataset)
Dataset release for the BMVC 2021 Paper "Few-Shot Domain Adaptation for Low Light RAW Image Enhancement" Abstract: Enhancing practical low light raw images is a difficult task due to severe noise and color distortions from short exposure…
1 paper · 2 benchmarks
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.
0 papers · 0 benchmarks
Low Light Dataset (Dataset with ill-lighting conditions DILCOD)
Introduced by Khan.
0 papers · 0 benchmarks
Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.