This paper reviews the extreme video super-resolution challenge from the AIM 2019 workshop, with emphasis on submitted solutions and results. Video extreme super-resolution x16 is a highly challenging problem, because 256 pixels need to be estimated for each single pixel in the low-resolution (LR) input. Contrary to single image super-resolution (SISR), video provides temporal information, which can be additionally leveraged to restore the heavily downscaled videos and is imperative for any video super-resolution (VSR) method. The challenge is composed of two tracks, to find the best performing method for fully supervised VSR (track 1) and to find the solution which generates the perceptually best looking outputs (track 2). A new video dataset, called Vid3oC, is introduced together with the challenge.