26 citations · 71 across the 39 of their papers we have counts for
7 papers · 2 filters
Sequence-SOD: Bio-inspired Sequence-aware Spiking ObjectDetection for Event Cameras
Katharina Bendig, René Schuster, Didier Stricker
Event cameras follow a retina-inspired sensing principle, reporting local intensity changes asynchronously with hightemporal resolution and a wide dynamic range. Spiking Neural Net…
Bounding Box Label Propagation for Re-Annotation of Document Layout Analysis Datasets
Nick Jochum, Tobias Alt-Veit, Christian Schön +3
Datasets in practical document processing scenarios typically grow over time, and their class annotations undergo continuous refinement. This creates significant re-annotation effo…
MILE: Mixture of Incremental LoRA Experts for Continual Semantic Segmentation across Domains and Modalities
Shishir Muralidhara, Didier Stricker, René Schuster
Continual semantic segmentation requires models to adapt to new domains or modalities without sacrificing performance on previously learned tasks. Expert-based learning, in which t…
Sensor Generalization for Adaptive Sensing in Event-based Object Detection via Joint Distribution Training
Aheli Saha, René Schuster, Didier Stricker
Bio-inspired event cameras have recently attracted significant research due to their asynchronous and low-latency capabilities. These features provide a high dynamic range and sign…
LiREC-Net: A Target-Free and Learning-Based Network for LiDAR, RGB, and Event Calibration
Aditya Ranjan Dash, Ramy Battrawy, René Schuster +1
Advanced autonomous systems rely on multi-sensor fusion for safer and more robust perception. To enable effective fusion, calibrating directly from natural driving scenes (i.e., ta…
SF3D-RGB: Scene Flow Estimation from Monocular Camera and Sparse LiDAR
Rajai Alhimdiat, Ramy Battrawy, René Schuster +2
Scene flow estimation is an extremely important task in computer vision to support the perception of dynamic changes in the scene. For robust scene flow, learning-based approaches…