FovDots is a video quality dataset that contains simulated artifacts that are typical for foveated rendering methods. The video sequences contain moving dots (disks) of different luminance. The foveated rendering is simulated by sampling pixels more sparsely at large eccentricities, reconstructing missing pixels with an in-painting method, and then using a filter to reduce aliasing artifacts.

The dataset was used to calibrate and test FovVideoVDP: A visible difference predictor for wide field-of-view video.

The details of the dataset can be found in the paper:

Mantiuk, Rafał K., Gyorgy Denes, Alexandre Chapiro, Anton Kaplanyan, Gizem Rufo, Romain Bachy, Trisha Lian, and Anjul Patney. “FovVideoVDP : A Visible Difference Predictor for Wide Field-of-View Video.” ACM Transaction on Graphics 40, no. 4 (2021): 49. https://doi.org/10.1145/3450626.3459831.

and its supplementary materials, which can be found at:

https://www.cl.cam.ac.uk/research/rainbow/projects/fovvideovdp/