This repository implements the Super SloMo paper by Jiang et al., using a convolutional neural network to interpolate frames between existing video frames. The model learns to estimate optical flow and synthesize intermediate frames, enabling high-quality slow-motion video generation from standard frame-rate footage. It provides training code, pretrained models, and evaluation scripts with metrics like PSNR and SSIM.