1 citations · 1 across the 5 of their papers we have counts for
6 papers
Velocity and stroke rate reconstruction of canoe sprint team boats based on panned and zoomed video recordings
Julian Ziegler, Daniel Matthes, Finn Gerdts +5
Pacing strategies, defined by velocity and stroke rate profiles, are essential for peak performance in canoe sprint. While GPS is the gold standard for analysis, its limited availa…
SoccerNet 2025 Challenges Results
Silvio Giancola, Anthony Cioppa, Marc Gutiérrez-Pérez +115
The SoccerNet 2025 Challenges mark the fifth annual edition of the SoccerNet open benchmarking effort, dedicated to advancing computer vision research in football video understandi…
Utilizing Reinforcement Learning for Bottom-Up part-wise Reconstruction of 2D Wire-Frame Projections
Julian Ziegler, Patrick Frenzel, Mirco Fuchs
This work concerns itself with the task of reconstructing all edges of an arbitrary 3D wire-frame model projected to an image plane. We explore a bottom-up part-wise procedure unde…
Using deep neural networks to detect non-analytically defined expert event labels in canoe sprint force sensor signals
Sarah Rockstroh, Patrick Frenzel, Daniel Matthes +3
Assessing an athlete's performance in canoe sprint is often established by measuring a variety of kinematic parameters during training sessions. Many of these parameters are relate…
Assessment of deep learning based blood pressure prediction from PPG and rPPG signals
Fabian Schrumpf, Patrick Frenzel, Christoph Aust +2
Exploiting photoplethysmography signals (PPG) for non-invasive blood pressure (BP) measurement is interesting for various reasons. First, PPG can easily be measured using fingercli…
Utilizing Mask R-CNN for Waterline Detection in Canoe Sprint Video Analysis
Marie-Sophie von Braun, Patrick Frenzel, Christian Käding +1
Determining a waterline in images recorded in canoe sprint training is an important component for the kinematic parameter analysis to assess an athlete's performance. Here, we prop…