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End-to-End learning of cost-volume aggregation for real-time dense stereo.

Andrey KuzminDmitry MikushinVictor S. Lempitsky
Published in: MLSP (2017)
Keyphrases
  • end to end
  • real time
  • dense stereo
  • reinforcement learning
  • admission control
  • congestion control
  • application layer