Zobrazeno 1 - 10
of 54
pro vyhledávání: '"Ackermann, Hanno"'
Standard imitation learning can fail when the expert demonstrators have different sensory inputs than the imitating agent. This is because partial observability gives rise to hidden confounders in the causal graph. In previous work, to work around th
Externí odkaz:
http://arxiv.org/abs/2211.02667
Dynamic scene graph generation aims at generating a scene graph of the given video. Compared to the task of scene graph generation from images, it is more challenging because of the dynamic relationships between objects and the temporal dependencies
Externí odkaz:
http://arxiv.org/abs/2107.12309
Humans perceive and construct the surrounding world as an arrangement of simple parametric models. In particular, man-made environments commonly consist of volumetric primitives such as cuboids or cylinders. Inferring these primitives is an important
Externí odkaz:
http://arxiv.org/abs/2105.02047
Semantic image understanding is a challenging topic in computer vision. It requires to detect all objects in an image, but also to identify all the relations between them. Detected objects, their labels and the discovered relations can be used to con
Externí odkaz:
http://arxiv.org/abs/2001.04735
Autor:
Kluger, Florian, Brachmann, Eric, Ackermann, Hanno, Rother, Carsten, Yang, Michael Ying, Rosenhahn, Bodo
We present a robust estimator for fitting multiple parametric models of the same form to noisy measurements. Applications include finding multiple vanishing points in man-made scenes, fitting planes to architectural imagery, or estimating multiple ri
Externí odkaz:
http://arxiv.org/abs/2001.02643
Image generating neural networks are mostly viewed as black boxes, where any change in the input can have a number of globally effective changes on the output. In this work, we propose a method for learning disentangled representations to allow for l
Externí odkaz:
http://arxiv.org/abs/1908.08989
The horizon line is an important geometric feature for many image processing and scene understanding tasks in computer vision. For instance, in navigation of autonomous vehicles or driver assistance, it can be used to improve 3D reconstruction as wel
Externí odkaz:
http://arxiv.org/abs/1907.10014
Autor:
Brandt, Sami S., Ackermann, Hanno
In this paper, we show that the affine, non-rigid structure-from-motion problem can be solved by rank-one, thus degenerate, basis shapes. It is a natural reformulation of the classic low-rank method by Bregler et al., where it was assumed that the de
Externí odkaz:
http://arxiv.org/abs/1904.13271
We propose a general, prior-free approach for the uncalibrated non-rigid structure-from-motion problem for modelling and analysis of non-rigid objects such as human faces. The word general refers to an approach that recovers the non-rigid affine stru
Externí odkaz:
http://arxiv.org/abs/1811.09132
In recent years, data-driven methods have shown great success for extracting information about the infrastructure in urban areas. These algorithms are usually trained on large datasets consisting of thousands or millions of labeled training examples.
Externí odkaz:
http://arxiv.org/abs/1709.05910