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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.CV2025
Decomposing Visual Classification: Assessing Tree-Based Reasoning in VLMs
Sary Elmansoury, Islam Mesabah, Gerrit GroÃmann +4
Vision language models (VLMs) excel at zero-shot visual classification, but their performance on fine-grained tasks and large hierarchical label spaces is understudied. This paper…
cs.CV2024
Ambiguous Annotations: When is a Pedestrian not a Pedestrian?
Luisa Schwirten, Jannes Scholz, Daniel Kondermann +1
Datasets labelled by human annotators are widely used in the training and testing of machine learning models. In recent years, researchers are increasingly paying attention to labe…