3 papers
cs.CV2026
Semi-Supervised Hierarchical Open-Set Classification
Erik Wallin, Fredrik Kahl, Lars Hammarstrand
Hierarchical open-set classification handles previously unseen classes by assigning them to the most appropriate high-level category in a class taxonomy. We extend this paradigm to…
cs.LG2025
ProHOC: Probabilistic Hierarchical Out-of-Distribution Classification via Multi-Depth Networks
Erik Wallin, Fredrik Kahl, Lars Hammarstrand
Out-of-distribution (OOD) detection in deep learning has traditionally been framed as a binary task, where samples are either classified as belonging to the known classes or marked…
cs.CV2024
Exploring Semi-Supervised Learning for Online Mapping
Adam Lilja, Erik Wallin, Junsheng Fu +1
The ability to generate online maps using only onboard sensory information is crucial for enabling autonomous driving beyond well-mapped areas. Training models for this task -- pre…