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Multi Task Learning On Cityscapes
評価指標
RMSE
mIoU
評価結果
このベンチマークにおける各モデルのパフォーマンス結果
| Paper Title | |||
|---|---|---|---|
| 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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