Mining Footprint Segmentation on Fine-grained (test)
92.33AccuracyMineC2FNet
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| MineC2FNetLearning Paradigm=MineC2FNet (ours)2026.05 | 92.33 | 84.1 | 73.64 | |
| FPNLearning Paradigm=Transfer Learning2026.05 | 90.65 | 80.06 | 68.26 | |
| LwMLearning Paradigm=Baseline Continual Learning2026.05 | 90.6 | 79.36 | 67.43 | |
| LwFLearning Paradigm=Baseline Continual Learning2026.05 | 90.22 | 78.94 | 67.02 | |
| DeepLabV3+Learning Paradigm=Transfer Learning2026.05 | 90.01 | 79.57 | 67.47 | |
| U-NetLearning Paradigm=Transfer Learning2026.05 | 89.79 | 79.52 | 67.26 | |
| GSMF-RS-DILLearning Paradigm=Domain Incremental Learning2026.05 | 88.83 | 85.02 | 71.25 | |
| ReplayLearning Paradigm=Baseline Continual Learning2026.05 | 88.81 | 76.5 | 63.61 | |
| MDIL-SSLearning Paradigm=Domain Incremental Learning2026.05 | 88.62 | 85.36 | 71.99 | |
| CCDALearning Paradigm=Class Incremental Learning2026.05 | 78.9 | 72.9 | 57 | |
| UDAforRSLearning Paradigm=Domain Adaptation2026.05 | 75.16 | 72.42 | 57.49 | |
| PrithviLearning Paradigm=Transfer Learning2026.05 | 66.14 | 66.21 | 49.74 | |
| BUSLearning Paradigm=Domain Adaptation2026.05 | 60.22 | 59.21 | 42.35 | |
| SPPALearning Paradigm=Class Incremental Learning2026.05 | 54.68 | 48.32 | 31.85 |