PWC-Net is an end-to-end trainable deep neural network for optical flow estimation, published at CVPR 2018. It fuses classic computer vision techniques—image pyramid, warping, and cost volume—into a single model to achieve state-of-the-art results. The repository provides implementations in both Caffe and PyTorch, nearly matching in accuracy.