6 papers
Uplifting Table Tennis: A Robust, Real-World Application for 3D Trajectory and Spin Estimation
Daniel Kienzle, Katja Ludwig, Julian Lorenz +2
Obtaining the precise 3D motion of a table tennis ball from standard monocular videos is a challenging problem, as existing methods trained on synthetic data struggle to generalize…
MMMS: Multi-Modal Multi-Surface Interactive Segmentation
Robin Schön, Julian Lorenz, Katja Ludwig +2
In this paper, we present a method to interactively create segmentation masks on the basis of user clicks. We pay particular attention to the segmentation of multiple surfaces that…
CoPa-SG: Dense Scene Graphs with Parametric and Proto-Relations
Julian Lorenz, Mrunmai Phatak, Robin Schön +4
2D scene graphs provide a structural and explainable framework for scene understanding. However, current work still struggles with the lack of accurate scene graph data. To overcom…
Efficient 2D to Full 3D Human Pose Uplifting including Joint Rotations
Katja Ludwig, Yuliia Oksymets, Robin Schön +2
In sports analytics, accurately capturing both the 3D locations and rotations of body joints is essential for understanding an athlete's biomechanics. While Human Mesh Recovery (HM…
Leveraging Anthropometric Measurements to Improve Human Mesh Estimation and Ensure Consistent Body Shapes
Katja Ludwig, Julian Lorenz, Daniel Kienzle +2
The basic body shape (i.e., the body shape in T-pose) of a person does not change within a single video. However, most SOTA human mesh estimation (HME) models output a slightly dif…
On the Importance of Conditioning for Privacy-Preserving Data Augmentation
Julian Lorenz, Katja Ludwig, Valentin Haug +1
Latent diffusion models can be used as a powerful augmentation method to artificially extend datasets for enhanced training. To the human eye, these augmented images look very diff…