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Models/YOLOP

YOLOP

Reported on 10 benchmarks across 4 tasks · 1 paper · 10 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision5 results

Drivable Area DetectiononBDD100K val
Params (M)· 2021-08-25
7.9
best: 38.9 (YOLOPv2)
SOTA
YOLOP: You Only Look Once for Panoptic Driving Perception arXiv:2108.11250
Drivable Area DetectiononBDD100K val
mIoU· 2021-08-25
91.5
best: 93.2 (YOLOPv2)
SOTA
YOLOP: You Only Look Once for Panoptic Driving Perception arXiv:2108.11250
Lane DetectiononBDD100K val
Accuracy (%)· 2021-08-25
70.5
best: 87.8 (YOLOPv2)
SOTA
YOLOP: You Only Look Once for Panoptic Driving Perception arXiv:2108.11250
Lane DetectiononBDD100K val
IoU (%)· 2021-08-25
26.2
best: 34.2 (TwinLiteNetPlus-Large)
SOTA
YOLOP: You Only Look Once for Panoptic Driving Perception arXiv:2108.11250
Lane DetectiononBDD100K val
Params (M)· 2021-08-25
7.9
best: 38.9 (YOLOPv2)
SOTA
YOLOP: You Only Look Once for Panoptic Driving Perception arXiv:2108.11250

Robots3 results

Autonomous VehiclesonBDD100K val
Accuracy (%)· 2021-08-25
70.5
best: 87.8 (YOLOPv2)
SOTA
YOLOP: You Only Look Once for Panoptic Driving Perception arXiv:2108.11250
Autonomous VehiclesonBDD100K val
IoU (%)· 2021-08-25
26.2
best: 34.2 (TwinLiteNetPlus-Large)
SOTA
YOLOP: You Only Look Once for Panoptic Driving Perception arXiv:2108.11250
Autonomous VehiclesonBDD100K val
Params (M)· 2021-08-25
7.9
best: 38.9 (YOLOPv2)
SOTA
YOLOP: You Only Look Once for Panoptic Driving Perception arXiv:2108.11250

Methodology2 results

2D Object DetectiononBDD100K val
Params (M)· 2021-08-25
7.9
best: 38.9 (YOLOPv2)
SOTA
YOLOP: You Only Look Once for Panoptic Driving Perception arXiv:2108.11250
2D Object DetectiononBDD100K val
mIoU· 2021-08-25
91.5
best: 93.2 (YOLOPv2)
SOTA
YOLOP: You Only Look Once for Panoptic Driving Perception arXiv:2108.11250