Pytorch unofficial reimplementation for "Spatial and semantic consistency regularizations for pedestrian attribute recognition", ICCV2021
PETA | mA | Acc | Prec | Recall | F1 |
---|---|---|---|---|---|
Paper SSC | 86.52 | 78.95 | 86.02 | 87.12 | 86.99 |
Unofficial SSC | 83.90 | 78.60 | 86.16 | 86.59 | 86.38 |
PA100K | mA | Acc | Prec | Recall | F1 |
---|---|---|---|---|---|
Paper SSC | 81.87 | 78.89 | 85.98 | 89.10 | 86.87 |
Unofficial SSC | 79.51 | 78.49 | 86.80 | 87.30 | 87.05 |
RAP | mA | Acc | Prec | Recall | F1 |
---|---|---|---|---|---|
Paper SSC | 82.77 | 68.37 | 75.05 | 87.49 | 80.43 |
Unofficial SSC | 82.14 | 68.16 | 77.87 | 82.88 | 79.87 |
You can download dataset from "https://github.com/valencebond/Rethinking_of_PAR".
${POSE_ROOT}
|-- data
|-- peta
|-- images/
|-- dataset_all.pkl
|-- rap
|-- RAP_dataset/
|-- dataset_all.pkl
|-- pa100k
|-- data/
|-- dataset_all.pkl
python tools/train.py --cfg experiments/[dataset name].yaml --gpu 0 -- savename [save path of outputs]