Devon: Deformable Volume Network for Learning Optical Flow

Yao Lu, Jack Valmadre, Heng Wang, Juho Kannala, Mehrtash Harandi, Philip H. S. Torr; Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 2018, pp. 0-0

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.

Related Material

[pdf] [arXiv]
[bibtex]
@InProceedings{Lu_2018_ECCV_Workshops,
author = {Lu, Yao and Valmadre, Jack and Wang, Heng and Kannala, Juho and Harandi, Mehrtash and Torr, Philip H. S.},
title = {Devon: Deformable Volume Network for Learning Optical Flow},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV) Workshops},
month = {September},
year = {2018}
}