43 citations · 86 across the 7 of their papers we have counts for
7 papers
Learning Task-Specific Generalized Convolutions in the Permutohedral Lattice
Anne S. Wannenwetsch, Martin Kiefel, Peter V. Gehler +1
Dense prediction tasks typically employ encoder-decoder architectures, but the prevalent convolutions in the decoder are not image-adaptive and can lead to boundary artifacts. Diff…
Unite the People: Closing the Loop Between 3D and 2D Human Representations
Christoph Lassner, Javier Romero, Martin Kiefel +3
3D models provide a common ground for different representations of human bodies. In turn, robust 2D estimation has proven to be a powerful tool to obtain 3D fits "in-the- wild". Ho…
Superpixel Convolutional Networks using Bilateral Inceptions
Raghudeep Gadde, Varun Jampani, Martin Kiefel +2
In this paper we propose a CNN architecture for semantic image segmentation. We introduce a new 'bilateral inception' module that can be inserted in existing CNN architectures and…
Semantic Instance Annotation of Street Scenes by 3D to 2D Label Transfer
Jun Xie, Martin Kiefel, Ming-Ting Sun +1
Semantic annotations are vital for training models for object recognition, semantic segmentation or scene understanding. Unfortunately, pixelwise annotation of images at very large…
Learning Sparse High Dimensional Filters: Image Filtering, Dense CRFs and Bilateral Neural Networks
Varun Jampani, Martin Kiefel, Peter V. Gehler
Bilateral filters have wide spread use due to their edge-preserving properties. The common use case is to manually choose a parametric filter type, usually a Gaussian filter. In th…
Permutohedral Lattice CNNs
Martin Kiefel, Varun Jampani, Peter V. Gehler
This paper presents a convolutional layer that is able to process sparse input features. As an example, for image recognition problems this allows an efficient filtering of signals…
Quasi-Newton Methods: A New Direction
Philipp Hennig, Martin Kiefel
Four decades after their invention, quasi-Newton methods are still state of the art in unconstrained numerical optimization. Although not usually interpreted thus, these are learni…