23 citations · 30 across the 5 of their papers we have counts for
5 papers
COOkeD: Ensemble-based OOD detection in the era of zero-shot CLIP
Galadrielle Humblot-Renaux, Gianni Franchi, Sergio Escalera +1
Out-of-distribution (OOD) detection is an important building block in trustworthy image recognition systems as unknown classes may arise at test-time. OOD detection methods typical…
A noisy elephant in the room: Is your out-of-distribution detector robust to label noise?
Galadrielle Humblot-Renaux, Sergio Escalera, Thomas B. Moeslund
The ability to detect unfamiliar or unexpected images is essential for safe deployment of computer vision systems. In the context of classification, the task of detecting images ou…
Beyond AUROC & co. for evaluating out-of-distribution detection performance
Galadrielle Humblot-Renaux, Sergio Escalera, Thomas B. Moeslund
While there has been a growing research interest in developing out-of-distribution (OOD) detection methods, there has been comparably little discussion around how these methods sho…
From CAD models to soft point cloud labels: An automatic annotation pipeline for cheaply supervised 3D semantic segmentation
Galadrielle Humblot-Renaux, Simon Buus Jensen, Andreas Møgelmose
We propose a fully automatic annotation scheme that takes a raw 3D point cloud with a set of fitted CAD models as input and outputs convincing point-wise labels that can be used as…
Navigation-Oriented Scene Understanding for Robotic Autonomy: Learning to Segment Driveability in Egocentric Images
Galadrielle Humblot-Renaux, Letizia Marchegiani, Thomas B. Moeslund +1
This work tackles scene understanding for outdoor robotic navigation, solely relying on images captured by an on-board camera. Conventional visual scene understanding interprets th…