Xianmei Lei — accepted AI-conference papers

2025

COARSE: Collaborative Pseudo-Labeling with Coarse Real Labels for Off-Road Semantic Segmentation

Aurelio Noca, Xianmei Lei, Jonathan Becktor, Jeffrey A. Edlund, Anna Sabel, Patrick Spieler +3

IROS 2025

Autonomous off-road navigation faces challenges due to diverse, unstructured environments, requiring robust perception with both geometric and semantic understanding. However, scarce densely labeled semantic data limits generalization across domains. Simulated data helps, but introduces domain adapt

Cited by 0 Source ↗Scholar ↗

2022

Early Recall, Late Precision: Multi-Robot Semantic Object Mapping under Operational Constraints in Perceptually-Degraded Environments

Xianmei Lei, Taeyeon Kim, Nicolas Marchal, Daniel Pastor, Barry Ridge, Frederik Schöller +6

IROS 2022poster

Semantic object mapping in uncertain, perceptually degraded environments during long-range multi-robot autonomous exploration tasks such as search-and-rescue is important and challenging. During such missions, high recall is desirable to avoid missing true target objects and high precision is also c…

Cited by 5 Source ↗Scholar ↗