Computer-generated video sequences with a frame-rate higher than the usual 24 images per second, such as 48 or 60 frames per second, have become more popular in the respective industries, due to more visual fidelity. This, however, results in more computational costs for the same length of the video sequence. One solution to this problem is the so-called frame-rate upsampling, which makes use of temporal and spatial coherence to approximate new frames and therefore saves computational time. Several methods have been published in this field, for the purposes of real-time rendering as well as for offline rendering algorithms. In this thesis, two new algorithms for fame-rate upsampling are introduced. Those are targeted at high-quality computer-generated images that feature various globalillumination effects. The two new algorithms make use of a video denoising method - the non-local means algorithm - to find the appropriate pixel colors for the frame, that has to be upsampled. To find the corresponding pixels in another frame, the methods of this thesis either use existing color information or require additional data, which can be extracted from any global-illumination algorithm with minimal further computations. The proposed methods are aimed at handling reflections and refractions in the scene better than previous work.