  In this report, we present our optical flow approach, MS-RAFT+, that won the
Robust Vision Challenge 2022. It is based on the MS-RAFT method, which
successfully integrates several multi-scale concepts into single-scale RAFT.
Our approach extends this method by exploiting an additional finer scale for
estimating the flow, which is made feasible by on-demand cost computation. This
way, it can not only operate at half the original resolution, but also use
MS-RAFT's shared convex upsampler to obtain full resolution flow. Moreover, our
approach relies on an adjusted fine-tuning scheme during training. This in turn
aims at improving the generalization across benchmarks. Among all participating
methods in the Robust Vision Challenge, our approach ranks first on VIPER and
second on KITTI, Sintel, and Middlebury, resulting in the first place of the
overall ranking.
