activity
20172026
most citedCombining Stereo Disparity and Optical Flow for Basic Scene Flow

26 citations · 71 across the 39 of their papers we have counts for

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Showing 2026Show all

8 papers · 1 filter

cs.LG2026

Layers Matter: Why Continual Learning Regularization Should Be Layer-Adaptive

Brian B. Moser, Ahmed Anwar, Tobias Christian Nauen +5

Continual learning regularizers like EWC fight forgetting by penalizing changes from previous-task parameters with per-parameter importance, typically diagonal Fisher values. Per-p…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…