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David Brüggemann

4 accepted papers

2025

GEM: A Generalizable Ego-Vision Multimodal World Model for Fine-Grained Ego-Motion, Object Dynamics, and Scene Composition Control

CVPR 2025poster

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, our model has precise control over object dynamics, ego-agent motion and human poses. GEM generates paired RGB and depth o…

2024

MUSES: The Multi-Sensor Semantic Perception Dataset for Driving under Uncertainty

ECCV 2024poster

"Achieving level-5 driving automation in autonomous vehicles necessitates a robust semantic visual perception system capable of parsing data from different sensors across diverse conditions. However, existing semantic perception datasets often lack important non-camera modalities typically used in a…

2023

Contrastive Model Adaptation for Cross-Condition Robustness in Semantic Segmentation

ICCV 2023poster

Standard unsupervised domain adaptation methods adapt models from a source to a target domain using labeled source data and unlabeled target data jointly. In model adaptation, on the other hand, access to the labeled source data is prohibited, i.e., only the source-trained model and unlabeled target…

Cited by 16PDFcodeScholar
2021

Exploring Relational Context for Multi-Task Dense Prediction

ICCV 2021poster

The timeline of computer vision research is marked with advances in learning and utilizing efficient contextual representations. Most of them, however, are targeted at improving model performance on a single downstream task. We consider a multi-task environment for dense prediction tasks, represente…

Cited by 97PDFcodeScholar