about ENLCA?

[fanrz]

thanks for your work. I have on question. in your paper, For each ordered sequence, we take the top n1N related ones as relevant features and n1N unrelated ones starting from n2N as irrelevant features. u use positive = torch.mean(score[:, :, :5], dim=2) negative = torch.mean(score[:, :, 50:], dim=2) # [N,H*W] why do you use 5 and 50?

[Zj-BinXia]

Sorry, we arrange the code after the paper being accepted. There may be the gap between the paper and code. You can change the code to "positive = torch.mean(score[:, :, :15], dim=2) negative = torch.mean(score[:, :, 50:65], dim=2) # [N,H*W] ".

[fanrz]

thank for your knid reply. I want to know for what reason, you pick 15 50 65. any explanation for the values? or observation of the training?

[Zj-BinXia]

observation of the training

[fanrz]

great, thanks