RAFT-MSF: Self-Supervised Monocular Scene Flow using Recurrent Optimizer. (arXiv:2205.01568v1 [cs.CV])

Learning scene flow from a monocular camera still remains a challenging task
due to its ill-posedness as well as lack of annotated data. Self-supervised
methods demonstrate learning scene flow estimation from unlabeled data, yet
their accuracy lags behind (semi-)supervised methods. In this paper, we
introduce a self-supervised monocular scene flow method that substantially
improves the accuracy over the previous approaches. Based on RAFT, a
state-of-the-art optical flow model, we design a new decoder to iteratively
update 3D motion fields and …

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