Multi Task Learning On Cityscapes
평가 지표
RMSE
mIoU
평가 결과
이 벤치마크에서 각 모델의 성능 결과
모델 이름 | 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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