| CondLSTR (ResNet-101) |
- F1 score
- 88.47
|
Generating Dynamic Kernels via Transformers for Lane Detection 2023-01-01 |
코드 1 |
| CondLSTR (ResNet-34) |
- F1 score
- 88.23
|
Generating Dynamic Kernels via Transformers for Lane Detection 2023-01-01 |
코드 1 |
| CondLSTR (ResNet-18) |
- F1 score
- 87.99
|
Generating Dynamic Kernels via Transformers for Lane Detection 2023-01-01 |
코드 1 |
| CANet-L |
- F1 score
- 87.87
- Precision
- 91.69
|
CANet: Curved Guide Line Network with Adaptive Decoder for Lane Detection 2023-04-23 |
연결 없음 |
| CLRNetV2 (ResNet101) |
- F1 score
- 87.81
|
CLRNetV2: A Faster and Stronger Lane Detector 2025-03-18 |
연결 없음 |
| CANet-M |
- F1 score
- 87.19
- Precision
- 91.53
- Recall
- 83.25
- GFLOPs
- 22.6
|
CANet: Curved Guide Line Network with Adaptive Decoder for Lane Detection 2023-04-23 |
연결 없음 |
| CANet-S |
- F1 score
- 86.57
- Precision
- 91.37
- Recall
- 82.25
- GFLOPs
- 13.1
|
CANet: Curved Guide Line Network with Adaptive Decoder for Lane Detection 2023-04-23 |
연결 없음 |
| CLRerNet-DLA34 |
- F1 score
- 86.47
- Precision
- 91.66
- Recall
- 81.83
- GFLOPs
- 18.4
|
CLRerNet: Improving Confidence of Lane Detection with LaneIoU 2023-05-15 |
코드 1 · 코드 2 |
| CLRNet-DLA34 |
- F1 score
- 86.1
- Precision
- 91.4
- Recall
- 81.39
- GFLOPs
- 18.4
|
CLRerNet: Improving Confidence of Lane Detection with LaneIoU 2023-05-15 |
코드 1 · 코드 2 |
| CondLaneNet-L(ResNet-101) |
- F1 score
- 86.10
- Precision
- 88.98
- Recall
- 83.41
- GFLOPs
- 44.9
- FPS
- 48
|
CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution 2021-05-11 |
코드 1 · 코드 2 · 코드 3 · 코드 4 |
| CondLaneNet-M(ResNet-34) |
- F1 score
- 85.92
- Precision
- 88.29
- Recall
- 83.68
- GFLOPs
- 19.7
- FPS
- 109
|
CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution 2021-05-11 |
코드 1 · 코드 2 · 코드 3 · 코드 4 |
| CondLaneNet-S(ResNet-18) |
- F1 score
- 85.09
- Precision
- 87.75
- Recall
- 82.58
- GFLOPs
- 10.3
- FPS
- 154
|
CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution 2021-05-11 |
코드 1 · 코드 2 · 코드 3 · 코드 4 |
| CurveLane-L |
- F1 score
- 82.29
- Precision
- 91.11
- Recall
- 75.03
- GFLOPs
- 20.7
|
CurveLane-NAS: Unifying Lane-Sensitive Architecture Search and Adaptive Point Blending 2020-07-23 |
코드 1 |
| CurveLane-M |
- F1 score
- 81.8
- Precision
- 93.49
- Recall
- 72.71
- GFLOPs
- 11.6
|
CurveLane-NAS: Unifying Lane-Sensitive Architecture Search and Adaptive Point Blending 2020-07-23 |
코드 1 |
| CurveLane-S |
- F1 score
- 81.12
- Precision
- 93.58
- Recall
- 71.59
- GFLOPs
- 7.4
|
CurveLane-NAS: Unifying Lane-Sensitive Architecture Search and Adaptive Point Blending 2020-07-23 |
코드 1 |
| PointLaneNet |
- F1 score
- 78.47
- Precision
- 86.33
- Recall
- 72.91
- GFLOPs
- 14.8
|
CurveLane-NAS: Unifying Lane-Sensitive Architecture Search and Adaptive Point Blending 2020-07-23 |
코드 1 |
| SCNN |
- F1 score
- 65.02
- Precision
- 76.13
- Recall
- 56.74
- GFLOPs
- 328.4
|
CurveLane-NAS: Unifying Lane-Sensitive Architecture Search and Adaptive Point Blending 2020-07-23 |
코드 1 |
| Enet-SAD |
- F1 score
- 50.31
- Precision
- 63.6
- Recall
- 41.6
- GFLOPs
- 3.9
|
CurveLane-NAS: Unifying Lane-Sensitive Architecture Search and Adaptive Point Blending 2020-07-23 |
코드 1 |
| CANet-L(ResNet101) |
- Recall
- 84.36
- GFLOPs
- 45.7
|
CANet: Curved Guide Line Network with Adaptive Decoder for Lane Detection 2023-04-23 |
연결 없음 |