FRCNN+FPN-Res50+refined feature map+Crowdhuman
Reported on 4 benchmarks across 2 tasks · 1 paper
Note: results are matched by exact model name. Different papers may use the same name for different model variants.
Robots2 results
- Reasonable Miss Rate· uses extra data· 2018-04-303.46best: 24.8 (LDCF)
- Reasonable MR^-2· uses extra data· 2018-04-3010.67best: 15.5 (TLL)
Computer Vision2 results
- Reasonable Miss Rate· uses extra data· 2018-04-303.46best: 24.8 (LDCF)
- Reasonable MR^-2· uses extra data· 2018-04-3010.67best: 15.5 (TLL)