person-re-ranking

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Question about the usage of q_q_dist

2

Hello! your reranking is a good job! However, there is a problem about your usage of q_q_dist. Without q_q_dist, it seems that your reranking would drop a lot. I do...

justopit

initial_rank = np.argsort(original_dist).astype(np.int32)

1

Hello! When I run the example ResNet-50 + Global Loss on Market1501, I met the error about Memory Error when it came to the Re-Ranking. Here is the link https://github.com/huanghoujing/AlignedReID-Re-Production-Pytorch....

PayneYong

HWNHJJ

First：download cuhk-03.mat and the new training/testing protocol split cuhk03_new_protocol_config_detected.mat cuhk03_new_protocol_config_labeled.mat, place all in the directory '/data/person-reid/cuhk03/' Second: I use my own code to generate the bounding_box_train query bounding_box_test, and Is...

HouBiaoLiu

How to generate Figure 7

2

Hi, can you please share the code to generate Figure 7 in your paper?

amena6490

你好，感谢作者的算法思想，但我对您的算法实现有些疑问 （最开始我用的是罗浩的python版本，他告诉我完全按您的matlab版本复现的） https://github.com/zhunzhong07/person-re-ranking/blob/master/evaluation/utils/re_ranking.m 1. 代码第10行 ` original_dist = original_dist./ repmat(max(original_dist, [], 2), 1, size(original_dist, 2));` 对距离矩阵如此处理的目的是什么？处理后，距离矩阵已经不是对称的了，并且转置后每一行的元素放缩的scale都不同 2. 代码6行 `[~, initial_rank] = sort(original_dist, 2, 'ascend');` 对整个query和gallery进行排序，会出现查询样本的k1互近邻中出现查询集样本，这和论文并不一致 另外我试了一下按论文思想，每次只传入1个query进行reranking的方法，这样可能会影响了query expansion，但结果似乎大部分情况都会比现在稍好一些（只是太慢） 3. 代码第31行 `V(i,...

zhxun00cn

maliho0803

Rank2~Rank10 dropped significantly ?

5

Hello, when I ran the code of this article, I found that Rank1 really improved, but why is Rank2~Rank10 dropped significantly ?

daichenchao

Thank you very much for your outstanding work. I have reproduced your code in the past few days. The accuracy is one or two percentage points lower than the one...

rmxhhh

batchsize

1

@zhunzhong07 Hi，i want to know your batchsize, but i cannot find it. Can you tell me the value of batchsize or where i can find it. Thank you very much.

rmxhhh