Open-World Semantic Segmentation Including Class Similarity
Statistik
この論文では、以下の数値が使用されています:
AUPR: 96.1%
FPR95: 6.9%
Kutipan
"Open-world or anomaly segmentation extends the anomaly detection task to a pixel-wise nature."
"Our approach is capable of distinguishing between different unknown classes."