1 citations · 2 across the 10 of their papers we have counts for
5 papers · 1 filter
Rate as a Feature, Not a Nuisance: Curriculum FiLM Training for Event-Based Graph Neural Networks
Kavyansh Tyagi, Andreas Ziegler
An event camera emits events at a rate given by the scene motion, object texture, illumination, its own contrast thresholds, and other settings. Across the N-Caltech101 dataset, re…
BlurBall: Joint Ball and Motion Blur Estimation for Table Tennis Ball Tracking
Thomas Gossard, Filip Radovic, Andreas Ziegler +1
Motion blur reduces the clarity of fast-moving objects, posing challenges for detection systems, especially in racket sports, where balls often appear as streaks rather than distin…
BiasBench: A reproducible benchmark for tuning the biases of event cameras
Andreas Ziegler, David Joseph, Thomas Gossard +2
Event-based cameras are bio-inspired sensors that detect light changes asynchronously for each pixel. They are increasingly used in fields like computer vision and robotics because…
TT3D: Table Tennis 3D Reconstruction
Thomas Gossard, Andreas Ziegler, Andreas Zell
Sports analysis requires processing large amounts of data, which is time-consuming and costly. Advancements in neural networks have significantly alleviated this burden, enabling h…
Table tennis ball spin estimation with an event camera
Thomas Gossard, Julian Krismer, Andreas Ziegler +2
Spin plays a pivotal role in ball-based sports. Estimating spin becomes a key skill due to its impact on the ball's trajectory and bouncing behavior. Spin cannot be observed direct…