11 citations · 24 across the 14 of their papers we have counts for
5 papers · 1 filter
DeepPrivacy: A Generative Adversarial Network for Face Anonymization
Håkon Hukkelås, Rudolf Mester, Frank Lindseth
We propose a novel architecture which is able to automatically anonymize faces in images while retaining the original data distribution. We ensure total anonymization of all faces…
Mono-SF: Multi-View Geometry Meets Single-View Depth for Monocular Scene Flow Estimation of Dynamic Traffic Scenes
Fabian Brickwedde, Steffen Abraham, Rudolf Mester
Existing 3D scene flow estimation methods provide the 3D geometry and 3D motion of a scene and gain a lot of interest, for example in the context of autonomous driving. These metho…
Mono-Stixels: Monocular depth reconstruction of dynamic street scenes
Fabian Brickwedde, Steffen Abraham, Rudolf Mester
In this paper we present mono-stixels, a compact environment representation specially designed for dynamic street scenes. Mono-stixels are a novel approach to estimate stixels from…
SDNet: Semantically Guided Depth Estimation Network
Matthias Ochs, Adrian Kretz, Rudolf Mester
Autonomous vehicles and robots require a full scene understanding of the environment to interact with it. Such a perception typically incorporates pixel-wise knowledge of the depth…
DistanceNet: Estimating Traveled Distance from Monocular Images using a Recurrent Convolutional Neural Network
Robin Kreuzig, Matthias Ochs, Rudolf Mester
Classical monocular vSLAM/VO methods suffer from the scale ambiguity problem. Hybrid approaches solve this problem by adding deep learning methods, for example by using depth maps…