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cs.CV2026
Efficient Image Annotation via Semi-Supervised Object Segmentation with Label Propagation
Vitalii Tutevych, Raphael Memmesheimer, Luca Eichler +4
Reliable object perception is necessary for general-purpose service robots. Open-vocabulary detectors struggle to generalize beyond a few classes and fully supervised training of o…
cs.CV2025
LIAM: Multimodal Transformer for Language Instructions, Images, Actions and Semantic Maps
Yihao Wang, Raphael Memmesheimer, Sven Behnke
The availability of large language models and open-vocabulary object perception methods enables more flexibility for domestic service robots. The large variability of domestic task…
cs.CV2024
Person Segmentation and Action Classification for Multi-Channel Hemisphere Field of View LiDAR Sensors
Svetlana Seliunina, Artem Otelepko, Raphael Memmesheimer +1
Robots need to perceive persons in their surroundings for safety and to interact with them. In this paper, we present a person segmentation and action classification approach that…