Multi Task Learning On Cityscapes
Métriques
RMSE
mIoU
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | RMSE | mIoU | Paper Title | Repository |
---|---|---|---|---|
SwinMTL | 0.51 | 76.41 | SwinMTL: A Shared Architecture for Simultaneous Depth Estimation and Semantic Segmentation from Monocular Camera Images | |
Nash-MTL | - | 75.41 | Multi-Task Learning as a Bargaining Game | - |
MultiObjectiveOptimization | - | 66.63 | Multi-Task Learning as Multi-Objective Optimization |
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