2 citations · 2 across the 2 of their papers we have counts for
4 papers · 1 filter
Handling Missing Observations with an RNN-based Prediction-Update Cycle
Stefan Becker, Ronny Hug, Wolfgang Hübner +2
In tasks such as tracking, time-series data inevitably carry missing observations. While traditional tracking approaches can handle missing observations, recurrent neural networks…
An RNN-based IMM Filter Surrogate
Stefan Becker, Ronny Hug, Wolfgang Hübner +1
The problem of varying dynamics of tracked objects, such as pedestrians, is traditionally tackled with approaches like the Interacting Multiple Model (IMM) filter using a Bayesian…
An Evaluation of Trajectory Prediction Approaches and Notes on the TrajNet Benchmark
Stefan Becker, Ronny Hug, Wolfgang Hübner +1
In recent years, there is a shift from modeling the tracking problem based on Bayesian formulation towards using deep neural networks. Towards this end, in this paper the effective…
Particle-based pedestrian path prediction using LSTM-MDL models
Ronny Hug, Stefan Becker, Wolfgang Hübner +1
Recurrent neural networks are able to learn complex long-term relationships from sequential data and output a pdf over the state space. Therefore, recurrent models are a natural ch…