XR-DAVID: XR Display Artifact Video Dataset

A video quality dataset with XR (AR/VR) display distortions was created to measure the effect of display distortions, such as colour fringes or dithering, on image quality. The dataset consists of: * 14 reference videos at 1080p resolution, spanning real, rendered, and productivity content, which are typical for AR/VR applications. * 8 distortions (display artifacts): - Spatiotemporal dithering - Light source nonuniformity (LSNU) - Blur (MTF degradation) - Reduced contrast (elevated black level) - Waveguide nonuniformity (WGNU) - Dynamic correction error (DCE) - Color fringes - Chroma subsampling The quality was measured in a controlled pairwise comparison experiment with 77 participants. The conditions (pairs of video clips) were selected using the ASAP active sampling technique [1] and then scaled to JOD units under Thurstone Case V assumptions [2] using the pwcmp software (https://github.com/mantiuk/pwcmp). Reference images have JOD==10 and distorted ones have JOD values lower than 10 (except for noisy results). ColorVideoVDP: A visual difference predictor for image, video and display distortions. Rafal K. Mantiuk, Param Hanji, Maliha Ashraf, Yuta Asano, Alexandre Chapiro. In SIGGRAPH 2024 Technical Papers, Article 129 See README.md for more details.