From: Multiscale recurrent regression networks for face alignment
Method | LFPW | HELEN | CommonSet | ChallengingSet | FullSet |
---|---|---|---|---|---|
FPLL (Zhu and Ramanan 2012) | 8.29 | 8.16 | 8.22 | 18.33 | 10.20 |
DRMF (Asthana et al. 2013) | 6.57 | 6.70 | 6.65 | 19.79 | 9.22 |
RCPR (Burgos-Artizzu et al. 2013) | 6.56 | 5.93 | 6.18 | 17.26 | 8.35 |
GN-DPM (Tzimiropoulos and Pantic 2014) | 5.92 | 5.69 | 5.78 | – | – |
SDM (Xiong and la Torre 2013) | 5.67 | 5.50 | 5.57 | 15.40 | 7.50 |
CFAN (Zhang et al. 2014) | 5.44 | 5.53 | 5.50 | – | – |
ERT (Kazemi and Sullivan 2014) | – | – | – | – | 6.40 |
BPCPR (Sun et al. 2015) | – | – | 5.24 | 16.56 | 7.46 |
ESR (Cao et al. 2012) | – | – | 5.28 | 17.00 | 7.58 |
LBF (Ren et al. 2014) | – | – | 4.95 | 11.98 | 6.32 |
LBF fast (Ren et al. 2014) | – | – | 5.38 | 15.50 | 7.37 |
Deep reg (Shi et al. 2014) | – | – | 4.51 | 13.80 | 6.31 |
CFSS (Zhu et al. 2015) | 4.87 | 4.63 | 4.73 | 9.98 | 5.76 |
CFSS prac (Zhu et al. 2015) | 4.90 | 4.72 | 4.73 | 10.92 | 5.99 |
TCDCN (Zhang et al. 2016) | 4.57 | 4.60 | 4.80 | 8.60 | 5.54 |
MSRRN | 3.98 | 3.71 | 3.83 | 7.25 | 4.84 |