The Magnetic Resonance – Computed Tomography (MR-CT) Jordan University Hospital (JUH) dataset has been collected after receiving Institutional Review Board (IRB) approval of the hospital and consent forms have been obtained from all patients. All procedures followed are consistent with the ethics of handling patients’ data.
This is a collection of 2D and 3D images used for grayscale image processing tests. It includes at least 8 images of each of the following sizes:
Given the difficulty to handle planetary data we provide downloadable files in PNG format from the missions Chang'E-3 and Chang'E-4. In addition to a set of scripts to do the conversion given a different PDS4 Dataset.
Existing datasets for reflection symmetry detection contain shapes which are single contour shapes, thus they are not really challenging. We also need to consider how well a symmetry detector works on complex/compound shapes where traditional methods based on contour approach can not. On the other hand, there is only one symmetrical axes for every shape of this dataset. Therefore, this fails to evaluate how a symmetry detector works on a shape containing several symmetrical axis and how good the detection is when the number of symmetrical axis is unknown.
Our complex street scene(CSS) containing strong light and heavy shadow scenes mainly comes from the Kitti dataset. Our datasets are captured by driving around Karlsruhe's mid-size city, in rural areas, and on highways. We equipped a standard station wagon with two high-resolution color and grayscale video cameras. Up to 15 cars and 30 pedestrians are visible per image. We aim to verify the performance of the algorithm in specific and complex street scenes.
The color fractal images with correlated RGB color components were generated using the midpoint displacement alogrithm, using vectorial increments in the RGB color space, according to a multivariate Gaussian distribution specified by the variance-covariance matrix. This data set contains two sets of 25 color fractal images with two color components, of varying complexity expressed as the color fractal dimension, as a function of (i) the Hurst coefficient that was varied from 0.1 to 0.9 in steps of 0.2 and (ii) the correlation coefficient between the red and green color channels.
We introduce HUMAN4D, a large and multimodal 4D dataset that contains a variety of human activities simultaneously captured by a professional marker-based MoCap, a volumetric capture and an audio recording system. By capturing 2 female and 2 male professional actors performing various full-body movements and expressions, HUMAN4D provides a diverse set of motions and poses encountered as part of single- and multi-person daily, physical and social activities (jumping, dancing, etc.), along with multi-RGBD (mRGBD), volumetric and audio data. Despite the existence of multi-view color
This dataset is for light field image augmentaion. The dataset contains 100 pairs of light field image, each of them consists of "original" and "modified". "Original" is light field image with only background, "modified" is light field image with exactly same background and an object on it.
To improve reproductivity of our papar, we would upload experimental data and resources of evaluations.
