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 1 | ## Datasets for nighttime and low-light conditions. 
 2 | 
 3 | ### Object Detection
 4 | - [ExDark (Exclusively Dark Image Dataset)](https://github.com/cs-chan/Exclusively-Dark-Image-Dataset)  
 5 | -- Labelled  
 6 | -- Multiple objects are annotated. 
 7 | - [BDD100K: Night](https://bdd-data.berkeley.edu/)  
 8 | -- Labelled (Small Data)  
 9 | -- Cars and other vehicles are annotated.  
10 | 
11 | ### Face Detection
12 | - [DarkFace Dataset](https://flyywh.github.io/CVPRW2019LowLight/)  
13 | -- Labelled  
14 | -- 5400/600 images for train/val  
15 | -- Face detection in extremely low-light
16 | 
17 | ### People/Pedestrian Detection
18 | - [NightOwls Dataset](https://www.nightowls-dataset.org/)  
19 | -- Labelled  
20 | -- Pedestrian detection
21 | - [KAIST Multi-Spectral Dataset](https://soonminhwang.github.io/rgbt-ped-detection/data/)  
22 | -- Labelled  
23 | -- Pedestrian detection
24 | 
25 | 
26 | ### Pose Estimation  
27 | - [ExLPose Dataset](http://cg.postech.ac.kr/research/ExLPose/)  
28 | -- Labelled   
29 | -- Human 2D Pose estimation in extremely low-light   
30 |   
31 | ### Stereo Vision
32 | - [The Oxford RobotCar](https://robotcar-dataset.robots.ox.ac.uk/)  
33 | -- Unlabelled  
34 | -- Provides raw LIDAR based sparse depth maps. 
35 | - [DENSE: Gated2Depth](https://www.uni-ulm.de/en/in/driveu/projects/dense-datasets)  
36 | -- Unlabelled  
37 | -- Provides raw LIDAR based sparse depth maps
38 | - [DENSE: PixelAccurateDepthBenchmark](https://www.uni-ulm.de/en/in/driveu/projects/dense-datasets)  
39 | -- Labelled (Small Data)  
40 | -- 4 scenes with 10 images each. Each image comes with a pixel-accurate dense depth map.
41 | 
42 | ### Semantic Segmentation
43 | - [BDD100K: Night](https://bdd-data.berkeley.edu/)  
44 | -- Labelled (Small Data)  
45 | -- Semantic classes compatible with the [CityScapes](https://www.cityscapes-dataset.com/) dataset
46 | - [Dark Zurich](https://www.trace.ethz.ch/publications/2019/GCMA_UIoU/)  
47 | -- Unlabelled  
48 | -- Provides a small set of 50 labelled images for validation/test purposes.  
49 | -- Semantic classes compatible with the [CityScapes](https://www.cityscapes-dataset.com/) dataset
50 | - [NightCity](https://arxiv.org/pdf/2003.06883.pdf)  
51 | -- Yet to be published
52 | 


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