17 citations · 17 across the 4 of their papers we have counts for
7 papers
A Latent ODE Approach to Spatiotemporal Modeling of Cine Cardiac MRI
David Brüggemann, Ekaterina Krymova, Firat Özdemir +6
Cardiac magnetic resonance imaging (CMR) captures rich spatiotemporal information about ventricular structure and motion, but conventional risk models use only a few image-derived…
Country-wide, high-resolution monitoring of forest browning with Sentinel-2
Samantha Biegel, David Brüggemann, Francesco Grossi +3
Natural and anthropogenic disturbances are impacting the health of forests worldwide. Monitoring forest disturbances at scale is important to inform conservation efforts. Here, we…
GEM: A Generalizable Ego-Vision Multimodal World Model for Fine-Grained Ego-Motion, Object Dynamics, and Scene Composition Control
Mariam Hassan, Sebastian Stapf, Ahmad Rahimi +17
We present GEM, a Generalizable Ego-vision Multimodal world model that predicts future frames using a reference frame, sparse features, human poses, and ego-trajectories. Hence, ou…
MUSES: The Multi-Sensor Semantic Perception Dataset for Driving under Uncertainty
Tim Brödermann, David Bruggemann, Christos Sakaridis +4
Achieving level-5 driving automation in autonomous vehicles necessitates a robust semantic visual perception system capable of parsing data from different sensors across diverse co…
Refign: Align and Refine for Adaptation of Semantic Segmentation to Adverse Conditions
David Bruggemann, Christos Sakaridis, Prune Truong +1
Due to the scarcity of dense pixel-level semantic annotations for images recorded in adverse visual conditions, there has been a keen interest in unsupervised domain adaptation (UD…
L2E: Lasers to Events for 6-DoF Extrinsic Calibration of Lidars and Event Cameras
Kevin Ta, David Bruggemann, Tim Brödermann +2
As neuromorphic technology is maturing, its application to robotics and autonomous vehicle systems has become an area of active research. In particular, event cameras have emerged…
Automated Search for Resource-Efficient Branched Multi-Task Networks
David Bruggemann, Menelaos Kanakis, Stamatios Georgoulis +1
The multi-modal nature of many vision problems calls for neural network architectures that can perform multiple tasks concurrently. Typically, such architectures have been handcraf…