Deep Network Based Frame Extrapolation With Reference Frame Alignment

Frame extrapolation is to predict future frames from the past (reference) frames, which has been studied intensively in the computer vision research and has great potential in video coding. Recently, a number of studies have been devoted to the use of deep networks for frame extrapolation, which achieves certain success. However, due to the complex and diverse motion patterns in natural video, it is still difficult to extrapolate frames with high fidelity directly from reference frames. To address this problem, we introduce reference frame alignment as a key technique for deep network-based frame extrapolation. We propose to align the reference frames, e.g. using block-based motion estimation and motion compensation, and then to extrapolate from the aligned frames by a trained deep network. Since the alignment, a preprocessing step, effectively reduces the diversity of network input, we observe that the network is …