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Pytorch code for our CVPR'19 (oral) work: Unsupervised person re-identification by soft multilabel learning

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Thank for your work. I set batchz-size is 100 or 184, and lr is 2e-5 or 1.414e-4, I got r1 0.000, r5 0.148 r10 0.208, map 5.395. And I have...

Thanks for your shareing of MSMT17 dataset. As the MSMT17 can not be downloaded from the official website, your sharing is really helpful. But, the processed data in '.Mat' format...

I tried to run the code,but I got the error. Traceback (most recent call last): File "src/main.py", line 46, in main() File "src/main.py", line 13, in main args.crop_size, args.padding, args.batch_size//2,...

==>>[2020-06-17 00:02:37] [Epoch=199/200] Stage 1, [Need: 00:03:45] Iter: [000/220] Freq 130.8 loss_source 0.000 loss_st 0.169 loss_target 0.304 loss_total 1.993 [2020-06-17 00:02:40] Iter: [100/220] Freq 360.5 loss_source 0.000 loss_st 0.163 loss_target...

Iter: [600/1348] Freq 248.2 loss_source 2.152 loss_st 0.781 loss_ml 3458.865 loss_target 0.000 loss_total 116.117 [2019-10-31 09:07:41] Iter: [700/1348] Freq 248.9 loss_source 2.127 loss_st 0.782 loss_ml 3387.675 loss_target 0.000 loss_total 114.824...