LSFM (Additional Data)
Reported on 8 benchmarks across 2 tasks
Note: results are matched by exact model name. Different papers may use the same name for different model variants.
Robots4 results
- Heavy MR^-2· uses extra data24.73best: 56.9 (RepLoss)
- Reasonable MR^-2· uses extra data6.38best: 15.5 (TLL)
- Small MR^-2· uses extra data7.9best: 25.6 (FRCNN)
- Test Time· uses extra data0.18best: 0.27 (ALFNet)
Computer Vision4 results
- Heavy MR^-2· uses extra data24.73best: 56.9 (RepLoss)
- Reasonable MR^-2· uses extra data6.38best: 15.5 (TLL)
- Small MR^-2· uses extra data7.9best: 25.6 (FRCNN)
- Test Time· uses extra data0.18best: 0.27 (ALFNet)