LER-YOLO reports 89.7% AP50 on the MBU benchmark for misaligned RGB-IR UAV detection by routing among RGB-dominant, IR-dominant, and fusion experts using a spatial reliability map.
Fusion Meets Diverse Conditions: A High-Diversity Benchmark and Baseline for UAV-Based Multimodal Object Detection with Condition Cues.arXiv2025
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
LER-YOLO: Reliability-Aware Expert Routing for Misaligned RGB-Infrared UAV Detection
LER-YOLO reports 89.7% AP50 on the MBU benchmark for misaligned RGB-IR UAV detection by routing among RGB-dominant, IR-dominant, and fusion experts using a spatial reliability map.