5 papers · 1 filter
Uplift and Upsample: Efficient 3D Human Pose Estimation with Uplifting Transformers
Moritz Einfalt, Katja Ludwig, Rainer Lienhart
The state-of-the-art for monocular 3D human pose estimation in videos is dominated by the paradigm of 2D-to-3D pose uplifting. While the uplifting methods themselves are rather eff…
Error Bounds of Projection Models in Weakly Supervised 3D Human Pose Estimation
Nikolas Klug, Moritz Einfalt, Stephan Brehm +1
The current state-of-the-art in monocular 3D human pose estimation is heavily influenced by weakly supervised methods. These allow 2D labels to be used to learn effective 3D human…
Decoupling Video and Human Motion: Towards Practical Event Detection in Athlete Recordings
Moritz Einfalt, Rainer Lienhart
In this paper we address the problem of motion event detection in athlete recordings from individual sports. In contrast to recent end-to-end approaches, we propose to use 2D human…
Mining Automatically Estimated Poses from Video Recordings of Top Athletes
Rainer Lienhart, Moritz Einfalt, Dan Zecha
Human pose detection systems based on state-of-the-art DNNs are on the go to be extended, adapted and re-trained to fit the application domain of specific sports. Therefore, plenty…
Activity-conditioned continuous human pose estimation for performance analysis of athletes using the example of swimming
Moritz Einfalt, Dan Zecha, Rainer Lienhart
In this paper we consider the problem of human pose estimation in real-world videos of swimmers. Swimming channels allow filming swimmers simultaneously above and below the water s…