GMFlow rethinks optical flow estimation as a global matching problem using a transformer architecture. The implementation provides feature extraction, feature enhancement, feature matching, flow propagation, and flow refinement components that can be combined modularly. Published at CVPR 2022 as an Oral presentation, it demonstrates competitive accuracy on benchmarks like Sintel with a streamlined pipeline.