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Models/SLTnet FPN-X101

SLTnet FPN-X101

Reported on 15 benchmarks across 5 tasks

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

Methodology12 results

  • 3DonUSC-GRAD-STDdb
    AP
    16.6
  • 3DonUSC-GRAD-STDdb
    AP 0.5
    44.9
  • 3DonImageNet VID
    MAP
    82.4
    best: 93.2 (YOLOV++)
  • 2D ClassificationonUSC-GRAD-STDdb
    AP
    16.6
  • 2D ClassificationonUSC-GRAD-STDdb
    AP 0.5
    44.9
  • 2D ClassificationonImageNet VID
    MAP
    82.4
    best: 93.2 (YOLOV++)
  • 2D Object DetectiononUSC-GRAD-STDdb
    AP
    16.6
  • 2D Object DetectiononUSC-GRAD-STDdb
    AP 0.5
    44.9
  • 2D Object DetectiononImageNet VID
    MAP
    82.4
    best: 93.2 (YOLOV++)
  • 16konUSC-GRAD-STDdb
    AP
    16.6
  • 16konUSC-GRAD-STDdb
    AP 0.5
    44.9
  • 16konImageNet VID
    MAP
    82.4
    best: 93.2 (YOLOV++)

Computer Vision3 results

  • Object DetectiononUSC-GRAD-STDdb
    AP
    16.6
  • Object DetectiononUSC-GRAD-STDdb
    AP 0.5
    44.9
  • Object DetectiononImageNet VID
    MAP
    82.4
    best: 93.2 (YOLOV++)