106 citations · 452 across the 92 of their papers we have counts for
3 papers · 2 filters
Unexplored flaws in multiple-choice VQA make benchmarking unreliable
Fabio Rosenthal, Sebastian Schmidt, Thorsten Graf +3
Previous works identify sensitivity to option order as a key issue in multiple-choice VQA (MC-VQA) evaluation and propose protocols to mitigate this effect. We show that such mitig…
A Machine Learning Perspective on Automated Driving Corner Cases
Sebastian Schmidt, Julius Körner, Stephan Günnemann
For high-stakes applications, like autonomous driving, a safe operation is necessary to prevent harm, accidents, and failures. Traditionally, difficult scenarios have been categori…
Joint Out-of-Distribution Filtering and Data Discovery Active Learning
Sebastian Schmidt, Leonard Schenk, Leo Schwinn +1
As the data demand for deep learning models increases, active learning (AL) becomes essential to strategically select samples for labeling, which maximizes data efficiency and redu…