# RAFT: Recurrent All-Pairs Field Transforms for Optical Flow

**Authors:** Zachary Teed, Jia Deng  
**arXiv:** [2003.12039](https://arxiv.org/abs/2003.12039)  
**Date:** 2020-03-26  
**Summary page:** https://www.summarizepaper.com/en/paper/2003.12039v1/

## Abstract

We introduce Recurrent All-Pairs Field Transforms (RAFT), a new deep network architecture for optical flow. RAFT extracts per-pixel features, builds multi-scale 4D correlation volumes for all pairs of pixels, and iteratively updates a flow field through a recurrent unit that performs lookups on the correlation volumes. RAFT achieves state-of-the-art performance, with strong cross-dataset generalization and high efficiency in inference time, training speed, and parameter count. Code is available \url{https://github.com/princeton-vl/RAFT}.