222 citations · 262 across the 7 of their papers we have counts for
7 papers
Normalizing Flows on the Product Space of SO(3) Manifolds for Probabilistic Human Pose Modeling
Olaf Dünkel, Tim Salzmann, Florian Pfaff
Normalizing flows have proven their efficacy for density estimation in Euclidean space, but their application to rotational representations, crucial in various domains such as robo…
Scene-Graph ViT: End-to-End Open-Vocabulary Visual Relationship Detection
Tim Salzmann, Markus Ryll, Alex Bewley +1
Visual relationship detection aims to identify objects and their relationships in images. Prior methods approach this task by adding separate relationship modules or decoders to ex…
Learning for CasADi: Data-driven Models in Numerical Optimization
Tim Salzmann, Jon Arrizabalaga, Joel Andersson +2
While real-world problems are often challenging to analyze analytically, deep learning excels in modeling complex processes from data. Existing optimization frameworks like CasADi…
Robots That Can See: Leveraging Human Pose for Trajectory Prediction
Tim Salzmann, Lewis Chiang, Markus Ryll +3
Anticipating the motion of all humans in dynamic environments such as homes and offices is critical to enable safe and effective robot navigation. Such spaces remain challenging as…
Motron: Multimodal Probabilistic Human Motion Forecasting
Tim Salzmann, Marco Pavone, Markus Ryll
Autonomous systems and humans are increasingly sharing the same space. Robots work side by side or even hand in hand with humans to balance each other's limitations. Such cooperati…
Real-time Neural-MPC: Deep Learning Model Predictive Control for Quadrotors and Agile Robotic Platforms
Tim Salzmann, Elia Kaufmann, Jon Arrizabalaga +3
Model Predictive Control (MPC) has become a popular framework in embedded control for high-performance autonomous systems. However, to achieve good control performance using MPC, a…
Trajectron++: Dynamically-Feasible Trajectory Forecasting With Heterogeneous Data
Tim Salzmann, Boris Ivanovic, Punarjay Chakravarty +1
Reasoning about human motion is an important prerequisite to safe and socially-aware robotic navigation. As a result, multi-agent behavior prediction has become a core component of…