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cs.CV2018
Disentangling Adversarial Robustness and Generalization
David Stutz, Matthias Hein, Bernt Schiele
Obtaining deep networks that are robust against adversarial examples and generalize well is an open problem. A recent hypothesis even states that both robust and accurate models ar…
cs.CV2018
Learning 3D Shape Completion under Weak Supervision
David Stutz, Andreas Geiger
We address the problem of 3D shape completion from sparse and noisy point clouds, a fundamental problem in computer vision and robotics. Recent approaches are either data-driven or…