Foreground-Background Segmentation on LSP (test) benchmark leaderboard · SOTA2 Research

Foreground-Background Segmentation on LSP (test)

92.79AccuracyPyMAF

Evaluation Results

Method	Links
PyMAF2021.03		92.79	0.89
Bodynet2019.05		92.75	0.84
BodyNet2021.03		92.75	0.84
PyMAF w/o AS2021.03		92.43	0.88
HKMR2021.03		92.23	0.88
SMPLify oracle2017.12		92.17	0.88
SMPLify oracle2019.05		92.17	0.88
SMPLify on [31]2019.05		92.17	0.88
SMPLify oracle2019.10		92.17	0.88
SMPLify on [35]2019.10		92.17	0.88
SMPLify2020.06		92.17	0.88
SMPLify2020.06		92.17	0.88
SMPLify oracle2021.03		92.17	0.88
SMPLify on [44]2021.03		92.17	0.88
DecoMR2020.06		92.1	0.88
DecoMR2021.03		92.1	0.88
SMPLify2017.12		91.89	0.88
SMPLify2019.05		91.89	0.88
SMPLify2019.10		91.89	0.88
SMPLify2020.06		91.89	0.88
SMPLify2021.03		91.89	0.88
SPIN2020.06		91.83	0.87
SPIN2021.03		91.83	0.87
TexturePose2019.10		91.82	0.87
TexturePose2021.03		91.82	0.87
HMR2017.12		91.67	0.87
HMR2019.05		91.67	0.87
HMR2019.10		91.67	0.87
HMR2020.06		91.67	0.87
HMR2021.03		91.67	0.87
Baseline2021.03		91.67	0.87
Ours (CMR)2019.05		91.46	0.87
CMR2020.06		91.46	0.87
CMR2021.03		91.46	0.87
HMR unpaired2017.12		91.3	0.86
Decision Forests2017.12		86.6	0.8