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    Workshop Focus and Aims

    Riemannian geometric computing has received a lot of recent interest in the computer vision community. In particular, Riemannian geometric principles can be applied to a variety of difficult computer vision problems including face recognition, activity recognition, object detection, biomedical image analysis, and structure-from-motion to name a few. Besides their nice mathematical formulation, Riemannian computations based on the geometry of underlying manifolds are often faster and more stable than their classical counterparts. Over the past few years, the popularity of Riemannian algorithms has increased several-fold. Some of the mathematical entities that benefit from a geometric analysis include rotation matrices, medial representations, subspace comparisons, symmetric positive-definite matrices, function spaces, and many more.

    Meet Our Team

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    Important dates

  • Paper Submission: March 25 April 3, 2016
  • Paper reviews due: April 15, 2016
  • Notification to authors: April 25, 2016
  • Camera-ready: May 2, 2016
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    Main topics of interest

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    Latest News


    Workshop program is available
    Paper Submission is extended
    Submission is open
    Diff-CV 2016 Workshop is accepted to be held in conjunction with CVPR 2016 in Las Vegas.

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