FSAF (ResNeXt-101, ImageNet-1k pretrain)

Reported on 5 benchmarks across 5 tasks

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

Methodology4 results

  • 3DonTBBR
    Average Recall@IoU:0.5-0.95
    38
    best: 45.4 (Swin-T (ImageNet-1k pretrain))
  • 2D ClassificationonTBBR
    Average Recall@IoU:0.5-0.95
    38
    best: 45.4 (Swin-T (ImageNet-1k pretrain))
  • 2D Object DetectiononTBBR
    Average Recall@IoU:0.5-0.95
    38
    best: 45.4 (Swin-T (ImageNet-1k pretrain))
  • 16konTBBR
    Average Recall@IoU:0.5-0.95
    38
    best: 45.4 (Swin-T (ImageNet-1k pretrain))

Computer Vision1 result