Abstract.Compressive sensing has been used to acquire the information in high-frame-rate video using low-frame-rate compressive measurements. Under the framework of coded aperture compressive temporal imaging, we propose a video reconstruction algorithm using Gaussian scale mixture model from temporal compressive measurements. Experimental results demonstrate that our proposed algorithm outperforms state-of-the-art algorithms in both peak signal-to-noise ratio and visual quality.