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The official implementation for Discover Cross-Modality Nuances for Visible-Infrared Person Re-Identification (CVPR21)

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I am interested in the visualization of learned features in this paper. ![image](https://user-images.githubusercontent.com/39946114/223644234-ae419821-e1ee-41d2-873e-67564b2ef0c2.png) Could you shared the code with me? Thank you!

How to get the visualization result like Fig.3?

I have tried multiple trainings with MPANet But it is consistently getting about 66% of Rank-1 in single shot and all mode of sysu dataset Is there any method to...

Hello,where can i get the features without dual path for TSNE ,like ‘ features/sysu/query-sysu-test-nodual-nore-adam-16x8-grey_model_150.mat’

I noticed that the Baidu Pan link of checkpoints has failed. Can you provide it again?

In the file 'MPANet/models/baseline.py', the 'train_forward' function calculates the final loss composed of multiple components. In the following code snippet, I notice that 'v_cls_loss' and 'i_cls_loss' are added twice. ```...

I was trying to get results but I don't have rand_perm_cam.mat file in my SYSU-dataset. Could you share your file or share its format.

Hi~ It's a nice job. The proposed CC loss seems to narrow the modality gap, which is often done by triplet loss. So, how about replacing CC with the triplet...