81 citations · 125 across the 11 of their papers we have counts for
14 papers
Towards Continual Motion-Language Agents: LoRA Variants for Incremental Motion Understanding and Generation
Bertram Taetz, Hugo Albuquerque Cosme da Silva, Gabriele Bleser-Taetz
Motion-language agents must possess the bidirectional capability to both understand human movement (motion-to-text, M2T) and generate it from natural language (text-to-motion, T2M)…
Amortized Inverse Kinematics via Graph Attention for Real-Time Human Avatar Animation
Muhammad Saif Ullah Khan, Chen-Yu Wang, Tim Prokosch +3
Inverse kinematics (IK) is a core operation in animation, robotics, and biomechanics: given Cartesian constraints, recover joint rotations under a known kinematic tree. In many rea…
Continual Learning for Image Captioning through Improved Image-Text Alignment
Bertram Taetz, Gal Bordelius
Generating accurate and coherent image captions in a continual learning setting remains a major challenge due to catastrophic forgetting and the difficulty of aligning evolving vis…
MinJointTracker: Real-time inertial kinematic chain tracking with joint position estimation and minimal state size
Michael Lorenz, Bertram Taetz, Gabriele Bleser-Taetz +1
Inertial motion capture is a promising approach for capturing motion outside the laboratory. However, as one major drawback, most of the current methods require different quantitie…
Breaking the mould of Social Mixed Reality - State-of-the-Art and Glossary
Marta Bieńkiewicz, Julia Ayache, Panayiotis Charalambous +15
This article explores a critical gap in Mixed Reality (MR) technology: while advances have been made, MR still struggles to authentically replicate human embodiment and socio-motor…
Autoencoder Attractors for Uncertainty Estimation
Steve Dias Da Cruz, Bertram Taetz, Thomas Stifter +1
The reliability assessment of a machine learning model's prediction is an important quantity for the deployment in safety critical applications. Not only can it be used to detect n…
Autoencoder for Synthetic to Real Generalization: From Simple to More Complex Scenes
Steve Dias Da Cruz, Bertram Taetz, Thomas Stifter +1
Learning on synthetic data and transferring the resulting properties to their real counterparts is an important challenge for reducing costs and increasing safety in machine learni…
Autoencoder Based Inter-Vehicle Generalization for In-Cabin Occupant Classification
Steve Dias Da Cruz, Bertram Taetz, Oliver Wasenmüller +2
Common domain shift problem formulations consider the integration of multiple source domains, or the target domain during training. Regarding the generalization of machine learning…
Illumination Normalization by Partially Impossible Encoder-Decoder Cost Function
Steve Dias Da Cruz, Bertram Taetz, Thomas Stifter +1
Images recorded during the lifetime of computer vision based systems undergo a wide range of illumination and environmental conditions affecting the reliability of previously train…
Flow Fields: Dense Correspondence Fields for Highly Accurate Large Displacement Optical Flow Estimation
Christian Bailer, Bertram Taetz, Didier Stricker
Modern large displacement optical flow algorithms usually use an initialization by either sparse descriptor matching techniques or dense approximate nearest neighbor fields. While…
Towards Self-Calibrating Inertial Body Motion Capture
Bertram Taetz, Gabriele Bleser, Markus Miezal
This paper presents a novel online capable method for simultaneous estimation of human motion in terms of segment orientations and positions along with sensor-to-segment calibratio…
Flow Fields: Dense Correspondence Fields for Highly Accurate Large Displacement Optical Flow Estimation
Christian Bailer, Bertram Taetz, Didier Stricker
Modern large displacement optical flow algorithms usually use an initialization by either sparse descriptor matching techniques or dense approximate nearest neighbor fields. While…
A high-order unstaggered constrained transport method for the 3D ideal magnetohydrodynamic equations based on the method of lines
Christiane Helzel, James A. Rossmanith, Bertram Taetz
Numerical methods for solving the ideal magnetohydrodynamic (MHD) equations in more than one space dimension must confront the challenge of controlling errors in the discrete diver…
An Unstaggered Constrained Transport Method for the 3D Ideal Magnetohydrodynamic Equations
Christiane Helzel, James A. Rossmanith, Bertram Taetz
Numerical methods for solving the ideal magnetohydrodynamic (MHD) equations in more than one space dimension must either confront the challenge of controlling errors in the discret…