Abstract
We propose a new neural network module, Deformable Cost Volume, for learning large displacement optical flow. The module does not distort the original images or their feature maps and therefore avoids the artifacts associated with warping. Based on this module, a new neural network model is proposed. The full version of this paper can be found online (https://arxiv.org/abs/1802.07351 ).
Cite
CITATION STYLE
Lu, Y., Valmadre, J., Wang, H., Kannala, J., Harandi, M., & Torr, P. H. S. (2019). Devon: Deformable volume network for learning optical flow. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11134 LNCS, pp. 673–677). Springer Verlag. https://doi.org/10.1007/978-3-030-11024-6_50
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