Yu-Wu

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https://github.com/Yu-Wu/One-Example-Person-ReID/blob/f792dde4330b9e7c42e2239ebe68afd1df05252d/my_reid/eug.py#L256-L300 Please see the code here.

@xiekun2019 Hi, the target is exactly the index i in the paper. It is used to figure out the i-th vector as indicated in the numerator. We do not use...

hi @Griffintaur You might misunderstand the code. I do retrain the network from scratch, but not more labeled data. The data for retraining consists of two sources: 1) the fixed...

Yes. The number of labeled data is fixed, while the number of unlabeled data with pseudo labels are growing. This is our strategy for semi-supervised learning.

The equation is the same with the paper. m_0 = 0 in at initial. Thus, m_i = i*p*nu. Here args.EF / 100 is exactly the same as p. For example,...

len(u_data) is a fixed number. You can print it in each iteration/step. u_data is generated at the beginning, and no further changes are applied on this variable in the following...

Data selection in each step is individual. So data selected in step t might also be selected in step t+1. We do not add any constrain on the data selection...

The second one. I add the pseudo labelled data at step t+1 only to the original labelled data ignoring the addition of pseudo labelled data done at step t. This...