In this work we present a deep learning framework for video compressive sensing.
This paper addresses the real-time encoding-decoding problem for high-frame-rate video compressive sensing (CS).
The measurement rate of cameras that take spatially multiplexed measurements by using spatial light modulators (SLM) is often limited by the switching speed of the SLMs.