Martin Kiefel
Position: PhD Student
Room no.: 1.A.20
Fax: +49 7071 601 552

I am interested in efficient inference methods for computer vision. What makes models stand out to allow fast inference and how push the computational burden towards training time? In particular, I am working on human pose estimation from single images, a challenging structured prediction problem.

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Conference Papers
  • M. Kiefel, P. Gehler (2014). Human Pose Estimation with Fields of Parts In: 13th European Conference on Computer Vision, (Ed) Fleet, D., Pajdla, T., Schiele, B., and Tuytelaars, T., LNCS 8693, Springer International Publishing, 331-346, ECCV 2014
Conference Papers
Conference Papers
  • P. Gehler, C. Rother, M. Kiefel, L. Zhang, B. Schölkopf (2011). Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance In: Advances in Neural Information Processing Systems 24, (Ed) J Shawe-Taylor and RS Zemel and PL Bartlett and FCN Pereira and KQ Weinberger, Curran Associates, Inc., Red Hook, NY, USA, 765-773, Twenty-Fifth Annual Conference on Neural Information Processing Systems (NIPS 2011)