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Devon: Deformable Volume Network for Learning Optical Flow

  • Yao LuEmail author
  • Jack Valmadre
  • Heng Wang
  • Juho Kannala
  • Mehrtash Harandi
  • Philip H. S. Torr
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11134)

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).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Yao Lu
    • 1
    • 2
    Email author
  • Jack Valmadre
    • 3
  • Heng Wang
    • 4
  • Juho Kannala
    • 5
  • Mehrtash Harandi
    • 6
  • Philip H. S. Torr
    • 3
  1. 1.Australian National UniversityCanberraAustralia
  2. 2.Data61, CSIROSydneyAustralia
  3. 3.University of OxfordOxfordUK
  4. 4.FacebookCambridgeUSA
  5. 5.Aalto UniversityHelsinkiFinland
  6. 6.Monash UniversityMelbourneAustralia

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