Lane Detection on CULane (test) (Robustness Evaluation)
85.51Benign AccuracyBadNets
Evaluation results
| Method | Links | ||||||
|---|---|---|---|---|---|---|---|
| BadNetsModel=ADNet2025.08 | 85.51 | 79.6 | 50.13 | 54.33 | 61.39 | 55.28 | |
| BlendedModel=ADNet2025.08 | 85.51 | 74.37 | 43.67 | 56.42 | 56.51 | 52.2 | |
| LD-AttackModel=ADNet2025.08 | 85.51 | 79.14 | 59.47 | 63.39 | 67.15 | 63.34 | |
| BadLANEModel=ADNet2025.08 | 85.51 | 85.46 | 36.61 | 61.16 | 65.95 | 54.57 | |
| DBALDModel=ADNet2025.08 | 85.51 | 82.37 | 66.49 | 64.82 | 68.17 | 66.5 | |
| BadNetsModel=RESA2025.08 | 78.98 | 76.68 | 71.08 | 58.68 | 69.14 | 66.3 | |
| BlendedModel=RESA2025.08 | 78.98 | 75.87 | 73.85 | 59.64 | 57.76 | 63.75 | |
| LD-AttackModel=RESA2025.08 | 78.98 | 71.35 | 73.26 | 64.77 | 69.18 | 69.07 | |
| BadLANEModel=RESA2025.08 | 78.98 | 72.81 | 75.39 | 62.94 | 68.23 | 68.85 | |
| DBALDModel=RESA2025.08 | 78.98 | 77.39 | 78.15 | 65.15 | 76.86 | 73.39 | |
| BadNetsModel=LaneATT2025.08 | 75.01 | 72.79 | 49.27 | 43.37 | 47.36 | 46.67 | |
| BlendedModel=LaneATT2025.08 | 75.01 | 73.15 | 57.14 | 59.07 | 47.04 | 54.41 | |
| LD-AttackModel=LaneATT2025.08 | 75.01 | 72.48 | 71.24 | 56.24 | 63.71 | 63.73 | |
| BadLANEModel=LaneATT2025.08 | 75.01 | 73.78 | 64.33 | 45.22 | 54.15 | 54.56 | |
| DBALDModel=LaneATT2025.08 | 75.01 | 74.2 | 81.65 | 73.45 | 74.19 | 76.41 | |
| BadNetsModel=SCNN2025.08 | 69.75 | 69.52 | 74.39 | 63.63 | 62.76 | 66.93 | |
| BlendedModel=SCNN2025.08 | 69.75 | 63.98 | 75.14 | 63.45 | 61.6 | 66.73 | |
| LD-AttackModel=SCNN2025.08 | 69.75 | 64.38 | 74.83 | 62.21 | 64.17 | 67.07 | |
| BadLaneModel=SCNN2025.08 | 69.75 | 67.57 | 72.28 | 63.96 | 62.94 | 66.39 | |
| DBALDModel=SCNN2025.08 | 69.75 | 68.75 | 76.19 | 67.34 | 68.69 | 70.74 |