Month: January 2019

DeepGUM presented at ECCV 2018

Our paper on robust regression was presented at ECCV’18 in Munich [1]. This paper presents a methodological framework for robust regression combining the representation power of deep architectures with the outlier detection capabilities of probabilistic models, in particular of a Gaussian-Uniform mixture (GUM). The code is available at https://github.com/Stephlat/DeepGUM. Abstract: In this paper we address the problem …