2 papers
cs.CV2026
From Label Error Detection to Correction: A Modular Framework and Benchmark for Object Detection Datasets
Sarina Penquitt, Jonathan Klees, Rinor Cakaj +3
Object detection has advanced rapidly in recent years, driven by increasingly large and diverse datasets. However, label errors often compromise the quality of these datasets and a…
cs.LG2025
Learning to Detect Label Errors by Making Them: A Method for Segmentation and Object Detection Datasets
Sarina Penquitt, Tobias Riedlinger, Timo Heller +2
Recently, detection of label errors and improvement of label quality in datasets for supervised learning tasks has become an increasingly important goal in both research and indust…