Perceptual Similarity is a dataset of human perceptual similarity judgments.
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The Vimeo-90K is a large-scale high-quality video dataset for lower-level video processing. It proposes three different video processing tasks: frame interpolation, video denoising/deblocking, and video super-resolution.
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xView is one of the largest publicly available datasets of overhead imagery. It contains images from complex scenes around the world, annotated using bounding boxes. It contains over 1M object instances from 60 different classes.
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The PIRM dataset consists of 200 images, which are divided into two equal sets for validation and testing. These images cover diverse contents, including people, objects, environments, flora, natural scenery, etc. Images vary in size, and are typically ~300K pixels in resolution.
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The General-100 dataset is a dataset for image super-resolution. It contains 100 bmp format images with no compression) The size of the 100 images ranges from 710 x 704 (large) to 131 x 112 (small).
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Contains 1024 pairs of high-quality images and covers diverse scenarios.
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IXI Dataset is a collection of 600 MR brain images from normal, healthy subjects. The MR image acquisition protocol for each subject includes:
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An in-the-wild stereo image dataset, comprising 49,368 image pairs contributed by users of the Holopix mobile social platform.
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TextZoom is a super-resolution dataset that consists of paired Low Resolution – High Resolution scene text images. The images are captured by cameras with different focal length in the wild.
QMUL-SurvFace is a surveillance face recognition benchmark that contains 463,507 face images of 15,573 distinct identities captured in real-world uncooperative surveillance scenes over wide space and time.
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A dataset consisting of stereo thermal, stereo color, and cross-modality image pairs with high accuracy ground truth (< 2mm) generated from a LiDAR. The authors scanned 100 cluttered indoor and 80 outdoor scenes featuring challenging environments and conditions. CATS contains approximately 1400 images of pedestrians, vehicles, electronics, and other thermally interesting objects in different environmental conditions, including nighttime, daytime, and foggy scenes.
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The PROBA-V Super-Resolution dataset is the official dataset of ESA's Kelvins competition for "PROBA-V Super Resolution". It contains satellite data from 74 hand-selected regions around the globe at different points in time. The data is composed of radiometrically and geometrically corrected Top-Of-Atmosphere (TOA) reflectances for the RED and NIR spectral bands at 300m and 100m resolution in Plate Carrée projection. The 300m resolution data is delivered as 128x128 grey-scale pixel images, the 100m resolution data as 384x384 grey-scale pixel images. Additionally, a quality map is provided for each pixel, indicating whether the pixels are concealed (i.e. by clouads, ice, water, missing information, etc.).
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The Stanford Light Field Archive is a collection of several light fields for research in computer graphics and vision.
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20 real low-resolution images selected from existing datasets or downloaded from internet
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Botswana is a hyperspectral image classification dataset. The NASA EO-1 satellite acquired a sequence of data over the Okavango Delta, Botswana in 2001-2004. The Hyperion sensor on EO-1 acquires data at 30 m pixel resolution over a 7.7 km strip in 242 bands covering the 400-2500 nm portion of the spectrum in 10 nm windows. Preprocessing of the data was performed by the UT Center for Space Research to mitigate the effects of bad detectors, inter-detector miscalibration, and intermittent anomalies. Uncalibrated and noisy bands that cover water absorption features were removed, and the remaining 145 bands were included as candidate features: [10-55, 82-97, 102-119, 134-164, 187-220]. The data analyzed in this study, acquired May 31, 2001, consist of observations from 14 identified classes representing the land cover types in seasonal swamps, occasional swamps, and drier woodlands located in the distal portion of the Delta.
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DRealSR establishes a Super Resolution (SR) benchmark with diverse real-world degradation processes, mitigating the limitations of conventional simulated image degradation.
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OST300 is an outdoor scene dataset with 300 test images of outdoor scenes, and a training set of 7 categories of images with rich textures.
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Pavia Centre is a hyperspectral dataset acquired by the ROSIS sensor during a flight campaign over Pavia, northern Italy. The number of spectral bands is 102 for Pavia Centre. Pavia Centre is a 1096*1096 pixels image. The geometric resolution is 1.3 meters. Image groundtruths differentiate 9 classes each. Pavia scenes were provided by Prof. Paolo Gamba from the Telecommunications and Remote Sensing Laboratory, Pavia university (Italy).
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StereoMSI comprises of 350 registered colour-spectral image pairs. The dataset has been used for the two tracks of the PIRM2018 challenge.
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Alsat-2B is a remote sensing dataset of low and high spatial resolution images (10m and 2.5m respectively) for the single-image super-resolution task. The high-resolution images are obtained through pan-sharpening. The dataset has been created from 13 images captured by the Alsat-2B Earth observation satellite, where the image cover 13 different cities.
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A large-scale multi-scene dataset for stereo deblurring, containing 20,637 blurry-sharp stereo image pairs from 135 diverse sequences and their corresponding bidirectional disparities.
The INRIA Dense Light Field Dataset (DLFD) is a dataset for testing depth estimation methods in a light field. DLFD contains 39 scenes with disparity range [-4,4] pixels. The light fields are of spatial resolution 512 x 512 and angular resolution 9 x 9.
Advanced pixel shift technology is employed to perform a full color sampling of the image. Pixel shift technology takes four samples of the same image at nearly the same time, and physically controls the camera sensor to move one pixel horizontally or vertically at each sampling to capture all color information at each pixel. The pixel shift technology ensures that the sampled images follow the distribution of natural images sampled by the camera, and the full information of the color (R, Gr, Gb, B channel) is completely obtained without any need of interpolation. In this way, the collected RGB images are artifacts-free, which leads to better training results for demosaicing related tasks.
A collection of photographic and synthetic images intended for analysis of image processing techniques and quality assessment of displays.
Description K-pop Idol Dataset - Female (KID-F) is the first dataset of K-pop idol high quality face images. It consists of about 6,000 high quality face images at 512x512 resolution and identity labels for each image.
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