650 citations · 761 across the 16 of their papers we have counts for
6 papers · 1 filter
Neural Nearest Neighbors Networks
Tobias Plötz, Stefan Roth
Non-local methods exploiting the self-similarity of natural signals have been well studied, for example in image analysis and restoration. Existing approaches, however, rely on k-n…
Multi-view X-ray R-CNN
Jan-Martin O. Steitz, Faraz Saeedan, Stefan Roth
Motivated by the detection of prohibited objects in carry-on luggage as a part of avionic security screening, we develop a CNN-based object detection approach for multi-view X-ray…
Lightweight Probabilistic Deep Networks
Jochen Gast, Stefan Roth
Even though probabilistic treatments of neural networks have a long history, they have not found widespread use in practice. Sampling approaches are often too slow already for simp…
Matryoshka Networks: Predicting 3D Geometry via Nested Shape Layers
Stephan R. Richter, Stefan Roth
In this paper, we develop novel, efficient 2D encodings for 3D geometry, which enable reconstructing full 3D shapes from a single image at high resolution. The key idea is to pose…
Detail-Preserving Pooling in Deep Networks
Faraz Saeedan, Nicolas Weber, Michael Goesele +1
Most convolutional neural networks use some method for gradually downscaling the size of the hidden layers. This is commonly referred to as pooling, and is applied to reduce the nu…
Stochastic Variational Inference with Gradient Linearization
Tobias Plötz, Anne S. Wannenwetsch, Stefan Roth
Variational inference has experienced a recent surge in popularity owing to stochastic approaches, which have yielded practical tools for a wide range of model classes. A key benef…