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Lane Detection On Curvelanes

Métriques

F1 score

GFLOPs

Precision

Recall

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	F1 score	GFLOPs	Precision	Recall	Paper Title	Repository
CANet-S	86.57	13.1	91.37	82.25	CANet: Curved Guide Line Network with Adaptive Decoder for Lane Detection	-
CANet-M	87.19	22.6	91.53	83.25	CANet: Curved Guide Line Network with Adaptive Decoder for Lane Detection	-
Enet-SAD	50.31	3.9	63.6	41.6	CurveLane-NAS: Unifying Lane-Sensitive Architecture Search and Adaptive Point Blending
CondLaneNet-L(ResNet-101)	86.10	44.9	88.98	83.41	CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution
CANet-L(ResNet101)	-	45.7	-	84.36	CANet: Curved Guide Line Network with Adaptive Decoder for Lane Detection	-
CLRNet-DLA34	86.1	18.4	91.4	81.39	CLRerNet: Improving Confidence of Lane Detection with LaneIoU
SCNN	65.02	328.4	76.13	56.74	CurveLane-NAS: Unifying Lane-Sensitive Architecture Search and Adaptive Point Blending
CANet-L	87.87	-	91.69	-	CANet: Curved Guide Line Network with Adaptive Decoder for Lane Detection	-
CurveLane-S	81.12	7.4	93.58	71.59	CurveLane-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-DLA34	86.47	18.4	91.66	81.83	CLRerNet: Improving Confidence of Lane Detection with LaneIoU
PointLaneNet	78.47	14.8	86.33	72.91	CurveLane-NAS: Unifying Lane-Sensitive Architecture Search and Adaptive Point Blending
CurveLane-M	81.8	11.6	93.49	72.71	CurveLane-NAS: Unifying Lane-Sensitive Architecture Search and Adaptive Point Blending
CondLaneNet-M(ResNet-34)	85.92	19.7	88.29	83.68	CondLaneNet: 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-L	82.29	20.7	91.11	75.03	CurveLane-NAS: Unifying Lane-Sensitive Architecture Search and Adaptive Point Blending
CondLaneNet-S(ResNet-18)	85.09	10.3	87.75	82.58	CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution

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