测试结果有问题 about res2net-pose-estimation HOT 4 CLOSED

We follow the simple baseline to use their evaluation method. We intend to prove the effectiveness of Res2Net. You are welcomed to provide other avilable evaluation methods.

from res2net-pose-estimation.

See this issue.microsoft/human-pose-estimation.pytorch#55
You should set the USE_GT_BBOX opinion False in the config file https://github.com/gasvn/Res2Net-Pose-Estimation/blob/master/experiments/coco/res2net/res2net101_4s_26w_256x192_d256x3_adam_lr1e-3.yaml

from res2net-pose-estimation.

Thanks, it seems the author's config is not the config used to reproduce the reported results.
Still, according to the link you provided, the Res2Net based method outperform the baseline when using gt box.
pose_resnet_50 | 0.724 | 0.915 | 0.804 | 0.697 | 0.765
pose_res2net_50 | 0.737 | 0.925 | 0.814 | 0.708 | 0.782
we will update the performance based on both gt box and the person detector's results ASAP.

from res2net-pose-estimation.

We have updated the results based on both gt box and the person detector's results. Thanks again for your notification.

from res2net-pose-estimation.