Flickr-Faces-HQ (FFHQ) consists of 70,000 high-quality PNG images at 1024×1024 resolution and contains considerable variation in terms of age, ethnicity and image background. It also has good coverage of accessories such as eyeglasses, sunglasses, hats, etc. The images were crawled from Flickr, thus inheriting all the biases of that website, and automatically aligned and cropped using dlib. Only images under permissive licenses were collected. Various automatic filters were used to prune the set, and finally Amazon Mechanical Turk was used to remove the occasional statues, paintings, or photos of photos.
1,221 PAPERS • 16 BENCHMARKS
BSD is a dataset used frequently for image denoising and super-resolution. Of the subdatasets, BSD100 is aclassical image dataset having 100 test images proposed by Martin et al.. The dataset is composed of a large variety of images ranging from natural images to object-specific such as plants, people, food etc. BSD100 is the testing set of the Berkeley segmentation dataset BSD300.
639 PAPERS • 46 BENCHMARKS
The Urban100 dataset contains 100 images of urban scenes. It commonly used as a test set to evaluate the performance of super-resolution models. Image Source: http://vllab.ucmerced.edu/wlai24/LapSRN/
508 PAPERS • 24 BENCHMARKS
SIDD is an image denoising dataset containing 30,000 noisy images from 10 scenes under different lighting conditions using five representative smartphone cameras. Ground truth images are provided along with the noisy images.
206 PAPERS • 2 BENCHMARKS
The See-in-the-Dark (SID) dataset contains 5094 raw short-exposure images, each with a corresponding long-exposure reference image. Images were captured using two cameras: Sony α7SII and Fujifilm X-T2.
129 PAPERS • 3 BENCHMARKS
Color BSD68 dataset for image denoising benchmarks is part of The Berkeley Segmentation Dataset and Benchmark. It is used for measuring image denoising algorithms performance. It contains 68 images.
120 PAPERS • 16 BENCHMARKS
PolyU Dataset is a large dataset of real-world noisy images with reasonably obtained corresponding “ground truth” images. The basic idea is to capture the same and unchanged scene for many (e.g., 500) times and compute their mean image, which can be roughly taken as the “ground truth” image for the real-world noisy images. The rational of this strategy is that for each pixel, the noise is generated randomly larger or smaller than 0. Sampling the same pixel many times and computing the average value will approximate the truth pixel value and alleviate significantly the noise.
24 PAPERS • 1 BENCHMARK
Benchmarking Denoising Algorithms with Real Photographs
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Extreme low-light denoising (ELD) dataset that covers 10 indoor scenes and 4 camera devices from multiple brands (SonyA7S2, NikonD850, CanonEOS70D, CanonEOS700D). It has three levels (800, 1600, 3200) and two low light factors(100, 200) for noisy images, resulting in 240 (3×2×10×4) raw image pairs in total.
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The CRVD dataset consists of 55 groups of noisy-clean videos with ISO values ranging from 1600 to 25600.
19 PAPERS • 1 BENCHMARK
A holistic approach to cross-channel image noise modeling and its application to image denoising
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The Fluorescence Microscopy Denoising (FMD) dataset is dedicated to Poisson-Gaussian denoising. The dataset consists of 12,000 real fluorescence microscopy images obtained with commercial confocal, two-photon, and wide-field microscopes and representative biological samples such as cells, zebrafish, and mouse brain tissues. Image averaging is used to effectively obtain ground truth images and 60,000 noisy images with different noise levels.
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A dataset of color images corrupted by natural noise due to low-light conditions, together with spatially and intensity-aligned low noise images of the same scenes.
12 PAPERS • 1 BENCHMARK
SEN12MS-CR is a multi-modal and mono-temporal data set for cloud removal. It contains observations covering 175 globally distributed Regions of Interest recorded in one of four seasons throughout the year of 2018. For each region, paired and co-registered synthetic aperture radar (SAR) Sentinel-1 measurements as well as cloudy and cloud-free optical multi-spectral Sentinel-2 observations from European Space Agency's Copernicus mission are provided. The Sentinel satellites provide public access data and are among the most prominent satellites in Earth observation.
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An open dataset of real photographs with real noise, from identical scenes captured with varying ISO values. Most images are taken with a Fujifilm X-T1 and XF18-55mm, other photographers are encouraged to contribute images for a more diverse crowdsourced effort.
7 PAPERS • NO BENCHMARKS YET
SEN12MS-CR-TS is a multi-modal and multi-temporal data set for cloud removal. It contains time-series of paired and co-registered Sentinel-1 and cloudy as well as cloud-free Sentinel-2 data from European Space Agency's Copernicus mission. Each time series contains 30 cloudy and clear observations regularly sampled throughout the year 2018. Our multi-temporal data set is readily pre-processed and backward-compatible with SEN12MS-CR.
7 PAPERS • 1 BENCHMARK
Synthetic training set: This set is constructed in the following two steps and will be used for estimation/training purposes. i) 84,000 275 pixel x 400 pixel ground-truth fingerprint images without any noise or scratches, but with random transformations (at most five pixels translation and +/-10 degrees rotation) were generated by using the software Anguli: Synthetic Fingerprint Generator. ii) 84,000 275 pixel x 400 pixel degraded fingerprint images were generated by applying random artifacts (blur, brightness, contrast, elastic transformation, occlusion, scratch, resolution, rotation) and backgrounds to the ground-truth fingerprint images. In total, it contains 168,000 fingerprint images (84,000 fingerprints, and two impressions - one ground-truth and one degraded - per fingerprint).
1 PAPER • NO BENCHMARKS YET