52 citations · 97 across the 25 of their papers we have counts for
4 papers · 2 filters
Learning and Tracking the 3D Body Shape of Freely Moving Infants from RGB-D sequences
Nikolas Hesse, Sergi Pujades, Michael J. Black +3
Statistical models of the human body surface are generally learned from thousands of high-quality 3D scans in predefined poses to cover the wide variety of human body shapes and ar…
Stereo 3D Object Trajectory Reconstruction
Sebastian Bullinger, Christoph Bodensteiner, Michael Arens +1
We present a method to reconstruct the three-dimensional trajectory of a moving instance of a known object category using stereo video data. We track the two-dimensional shape of o…
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…