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TransCrowd: Weakly-Supervised Crowd Counting with Transformers [SCIS]

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![SharedScreenshot](https://user-images.githubusercontent.com/96060802/160965018-8d773909-3bf1-499e-8ebc-15cea82123a4.jpg) ![SharedScreenshot1](https://user-images.githubusercontent.com/96060802/160965021-2ff27a94-e60c-4674-9e08-009a1298fcbe.jpg)

没有提供prepare_nwpu.py 跟描述里面的不一样呢

` tuner_params = nni.get_next_parameter()`根据这个tuner_params为空,看来nni并没有调整参数呢,为什么要调这个呢

您好,最近想复现您的代码时候,根据readme中的指示,在train阶段发生报错,具体表现为: RuntimeError: stack expects each tensor to be equal size, but got [3, 384, 384] at entry 0 and [3, 768, 1152] at entry 1 尝试用transformer.Resize(384,384)解决无果,遂来询问。望解答

请问作者可以提供attention weight可视化的代码吗?从而方便后续工作分析网络在关注什么

I am very interested in your proposal and would love to use it. However, since I cannot create a Baidu account, can you distribute the trained model with other cloud...

In weakly-supervised counting, only the global crowd numbers are available. If you crop one image into several patches, there will be more supervision information, and the comparison may be unfair...

The performance cannot be reproduced. The experiment was conducted on Shanghaitech A, and the mae of the method using the token is 70.4, and the method using the gap is...

how can we generate the attetion weight map?