| SCNN_UNet_Attention_PL* |
- Accuracy
- 98.38
|
Robust Lane Detection through Self Pre-training with Masked Sequential Autoencoders and Fine-tuning with Customized PolyLoss 2023-05-26 |
연결 없음 |
| CLRNetV2 (ResNet18) |
- Accuracy
- 96.99
- F1 score
- 97.90
|
CLRNetV2: A Faster and Stronger Lane Detector 2025-03-18 |
연결 없음 |
| PE-RESA |
- Accuracy
- 96.93
|
Lane detection with Position Embedding 2022-03-23 |
연결 없음 |
| FOLOLane(ERFNet) |
- Accuracy
- 96.92
|
Focus on Local: Detecting Lane Marker from Bottom Up via Key Point 2021-05-28 |
연결 없음 |
| CLRNet(ResNet-34) |
- Accuracy
- 96.9%
- F1 score
- 97.82
|
CLRNet: Cross Layer Refinement Network for Lane Detection 2022-03-19 |
코드 1 · 코드 2 · 코드 3 · 코드 4 |
| CLRNetV2 (ResNet34) |
- Accuracy
- 96.88
- F1 score
- 97.95
|
CLRNetV2: A Faster and Stronger Lane Detector 2025-03-18 |
연결 없음 |
| CLRNet(ResNet-18) |
- Accuracy
- 96.82%
- F1 score
- 97.89
|
CLRNet: Cross Layer Refinement Network for Lane Detection 2022-03-19 |
코드 1 · 코드 2 · 코드 3 · 코드 4 |
| RESA |
- Accuracy
- 96.82
- F1 score
- 96.93
|
RESA: Recurrent Feature-Shift Aggregator for Lane Detection 2020-08-31 |
코드 1 · 코드 2 · 코드 3 · 코드 4 |
| CLLD |
- Accuracy
- 96.82
|
Contrastive Learning for Lane Detection via cross-similarity 2023-08-16 |
코드 1 · 코드 2 |
| CANet-L(ResNet101) |
- Accuracy
- 96.76%
- F1 score
- 97.77
|
CANet: Curved Guide Line Network with Adaptive Decoder for Lane Detection 2023-04-23 |
연결 없음 |
| CANet-M |
- Accuracy
- 96.66%
- F1 score
- 97.44
|
CANet: Curved Guide Line Network with Adaptive Decoder for Lane Detection 2023-04-23 |
연결 없음 |
| ENet-SAD |
- Accuracy
- 96.64%
- F1 score
- 95.92
|
Learning Lightweight Lane Detection CNNs by Self Attention Distillation 2019-08-02 |
코드 1 · 코드 2 |
| HarD-SP |
- Accuracy
- 96.58%
- F1 score
- 96.38
|
Towards Lightweight Lane Detection by Optimizing Spatial Embedding 2020-08-19 |
코드 1 |
| CANet-S |
- Accuracy
- 96.56%
- F1 score
- 97.51
|
CANet: Curved Guide Line Network with Adaptive Decoder for Lane Detection 2023-04-23 |
연결 없음 |
| CondLaneNet-L(ResNet-101) |
- Accuracy
- 96.54%
- F1 score
- 97.24
|
CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution 2021-05-11 |
코드 1 · 코드 2 · 코드 3 · 코드 4 |
| Oblique Convolution |
- Accuracy
- 96.50%
- F1 score
- 97.42
|
연결 없음 논문 날짜 미기재 |
연결 없음 |
| Pairwise pixel supervision + FCN |
- Accuracy
- 96.50%
- F1 score
- 94.31
|
Learning to Cluster for Proposal-Free Instance Segmentation 2018-03-17 |
코드 1 |
| EL-GAN |
- Accuracy
- 96.40%
- F1 score
- 96.26
|
EL-GAN: Embedding Loss Driven Generative Adversarial Networks for Lane Detection 2018-06-14 |
연결 없음 |
| LaneNet |
- Accuracy
- 96.4%
- F1 score
- 94.80
|
Towards End-to-End Lane Detection: an Instance Segmentation Approach 2018-02-15 |
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 · 코드 7 · 코드 8 · 코드 9 · 코드 10 · 코드 11 · 코드 12 · 코드 13 · 코드 14 · 코드 15 · 코드 16 · 코드 17 · 코드 18 · 코드 19 · 코드 20 · 코드 21 · 코드 22 |
| Discriminative loss function |
- Accuracy
- 96.40%
|
Semantic Instance Segmentation with a Discriminative Loss Function 2017-08-08 |
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 · 코드 7 · 코드 8 |
| ENet-Label |
- Accuracy
- 96.29%
- F1 score
- 95.23
|
Agnostic Lane Detection 2019-05-02 |
연결 없음 |
| R-34-E2E |
- Accuracy
- 96.22%
- F1 score
- 96.58
|
End-to-End Lane Marker Detection via Row-wise Classification 2020-05-06 |
코드 1 |
| LSTR |
- Accuracy
- 96.18
- F1 score
- 96.68
|
End-to-end Lane Shape Prediction with Transformers 2020-11-09 |
코드 1 · 코드 2 |
| R-50-E2E |
- Accuracy
- 96.11%
- F1 score
- 96.37
|
End-to-End Lane Marker Detection via Row-wise Classification 2020-05-06 |
코드 1 |
| LaneATT (ResNet-122) |
- Accuracy
- 96.10%
- F1 score
- 96.06
|
Keep your Eyes on the Lane: Real-time Attention-guided Lane Detection 2020-10-22 |
코드 1 · 코드 2 · 코드 3 |
| ERF-E2E |
- Accuracy
- 96.02%
- F1 score
- 96.25
|
End-to-End Lane Marker Detection via Row-wise Classification 2020-05-06 |
코드 1 |
| Lane-LSQ |
- Accuracy
- 95.84%
|
연결 없음 논문 날짜 미기재 |
연결 없음 |
| BézierLaneNet (ResNet-34) |
- Accuracy
- 95.65%
|
Rethinking Efficient Lane Detection via Curve Modeling 2022-03-04 |
코드 1 · 코드 2 |
| LaneAF |
- Accuracy
- 95.64%
- F1 score
- 96.49
|
LaneAF: Robust Multi-Lane Detection with Affinity Fields 2021-03-22 |
코드 1 |
| LaneATT (ResNet-34) |
- Accuracy
- 95.63%
- F1 score
- 96.77
|
Keep your Eyes on the Lane: Real-time Attention-guided Lane Detection 2020-10-22 |
코드 1 · 코드 2 · 코드 3 |