Comments (3)
Does it mean this repo only provides the variant "w/o SSTN+parallel SPPE" as described in table 3 of the paper and one cannot obtain the best performance reported in the paper (and the readme file) using this repo?
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Hi, it is not used in our torch model. We add a parallel SPPE when using the SSTN and it should be discarded during testing period. However, torch doesn't support loading part of the model during testing and this will affect our inference efficiency. Caffe supports loading part of the weights, thus you can find SSTN in our old repo: https://github.com/MVIG-SJTU/RMPE, which is implemented in Caffe
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using the SSTN and it should be discarded during testing period. So discarded SSTN results to 1% AP drop?? Why do you discard SSTN? @Fang-Haoshu
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