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Lane Detection On Curvelanes

评估指标

F1 score
GFLOPs
Precision
Recall

评测结果

各个模型在此基准测试上的表现结果

模型名称
F1 score
GFLOPs
Precision
Recall
Paper TitleRepository
CANet-S86.5713.191.3782.25CANet: Curved Guide Line Network with Adaptive Decoder for Lane Detection-
CANet-M87.1922.691.5383.25CANet: Curved Guide Line Network with Adaptive Decoder for Lane Detection-
Enet-SAD50.313.963.641.6CurveLane-NAS: Unifying Lane-Sensitive Architecture Search and Adaptive Point Blending
CondLaneNet-L(ResNet-101)86.1044.988.9883.41CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution
CANet-L(ResNet101)-45.7-84.36CANet: Curved Guide Line Network with Adaptive Decoder for Lane Detection-
CLRNet-DLA3486.118.491.481.39CLRerNet: Improving Confidence of Lane Detection with LaneIoU
SCNN65.02328.476.1356.74CurveLane-NAS: Unifying Lane-Sensitive Architecture Search and Adaptive Point Blending
CANet-L87.87-91.69-CANet: Curved Guide Line Network with Adaptive Decoder for Lane Detection-
CurveLane-S81.127.493.5871.59CurveLane-NAS: Unifying Lane-Sensitive Architecture Search and Adaptive Point Blending
CondLSTR (ResNet-101)88.47---Generating Dynamic Kernels via Transformers for Lane Detection
CondLSTR (ResNet-18)87.99---Generating Dynamic Kernels via Transformers for Lane Detection
CLRerNet-DLA3486.4718.491.6681.83CLRerNet: Improving Confidence of Lane Detection with LaneIoU
PointLaneNet78.4714.886.3372.91CurveLane-NAS: Unifying Lane-Sensitive Architecture Search and Adaptive Point Blending
CurveLane-M81.811.693.4972.71CurveLane-NAS: Unifying Lane-Sensitive Architecture Search and Adaptive Point Blending
CondLaneNet-M(ResNet-34)85.9219.788.2983.68CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution
CondLSTR (ResNet-34)88.23---Generating Dynamic Kernels via Transformers for Lane Detection
CurveLane-L82.2920.791.1175.03CurveLane-NAS: Unifying Lane-Sensitive Architecture Search and Adaptive Point Blending
CondLaneNet-S(ResNet-18)85.0910.387.7582.58CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution
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