Taking a Deeper Look at the Inverse Compositional Algorithm

CVPR 2019 Zhaoyang LvFrank DellaertJames M. RehgAndreas Geiger

In this paper, we provide a modern synthesis of the classic inverse compositional algorithm for dense image alignment. We first discuss the assumptions made by this well-established technique, and subsequently propose to relax these assumptions by incorporating data-driven priors into this model... (read more)

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