DCSL - Generalizable Crowd Counting via Diverse Context Style Learning

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Deep Learning DCSL
Overview

DCSL

Generalizable Crowd Counting via Diverse Context Style Learning

Requirement:

python==3.8

pytorch==1.9.1

Test_datasets

链接: https://pan.baidu.com/s/1kChZgPQRCF4x0rAskaDpZw 提取码: ddqp

Parameters:

链接: https://pan.baidu.com/s/1wkXIho0P3HQXBCOMuGopXA 提取码: gap8

Test:

You can run test.py to test the model.

When loading the training parameters trained on which dataset to test the model,please modify models/backbones/model.py: num_class=num_class_SHA or num_class_SHB or num_class_QNRF.

For example,when use SHA.pth,please set num_class=num_class_SHA

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Comments
  • IBN

    IBN

    作者,您好,我不是很理解你文中的这句话:“However, due to the fine-grained style discrepancy within a single image for crowd counting, IBN inevitably loses some fine-grained content information, affecting the generalization performance.”,您能帮我解惑一下吗?十分感谢

    opened by iaixuexi 0
Owner
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