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Models/TriLiteNet-base

TriLiteNet-base

Reported on 10 benchmarks across 4 tasks

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)
    2.35
    best: 38.9 (YOLOPv2)
  • Drivable Area DetectiononBDD100K val
    mIoU
    92.4
    best: 93.2 (YOLOPv2)
  • Lane DetectiononBDD100K val
    Accuracy (%)
    82.3
    best: 87.8 (YOLOPv2)
  • Lane DetectiononBDD100K val
    IoU (%)
    29.8
    best: 34.2 (TwinLiteNetPlus-Large)
  • Lane DetectiononBDD100K val
    Params (M)
    2.35
    best: 38.9 (YOLOPv2)

Robots3 results

  • Autonomous VehiclesonBDD100K val
    Accuracy (%)
    82.3
    best: 87.8 (YOLOPv2)
  • Autonomous VehiclesonBDD100K val
    IoU (%)
    29.8
    best: 34.2 (TwinLiteNetPlus-Large)
  • Autonomous VehiclesonBDD100K val
    Params (M)
    2.35
    best: 38.9 (YOLOPv2)

Methodology2 results

  • 2D Object DetectiononBDD100K val
    Params (M)
    2.35
    best: 38.9 (YOLOPv2)
  • 2D Object DetectiononBDD100K val
    mIoU
    92.4
    best: 93.2 (YOLOPv2)