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Few-Shot Scene Adaptive Crowd Counting Using Meta-Learning (WACV 2020)

Home Page: https://arxiv.org/abs/2002.00264

License: MIT License

Python 98.22% Shell 1.78%
crowd-counting few-shot-learning meta-learning pytorch

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yongliang-qiao

fscc's Issues

Pretrained CSRNet

Hey,
By pretrained CSRNet, do you mean Imagenet pretrained Vgg16 layers plus random initialization for rest of the CSRNet layers ? (Looks like the pretrained net is trained on world expo. If that's the case, could you please share the pretrained net as well ? )

Thanks,
Viresh

code help

Can you provide me with the code of the comparison experiment(Reptile and Meta-LSTM)? This will reduce my workload

Preprocessing on the dataset

Hi,

Great application of MAML. I wonder if you haven't released some preprocessing operations. I found I cannot directly run the code, The original dataset has not been divided into 'tasks (classes)', so I will get errors in the get_task.py.
Hope to hear from you.

Best.

About dataset

Could you share the structure of WorldExpo'10 dataset?
I want to know the train, test data file structure.
And Could you provide sample annotation file? I don't know how the annotation file is organized.
If you could share the dataset structure and sample annotation file, it will be very helpful for me.

Pretrained model for CSRNet

In meta_learner.py, there are # TODO: path of the pre-trained backbone CSRNet.
In the paper, the model use VGG-16 pretrained model on ImageNet. Does pretrained backbone CSRNet mean the VGG-16 pretrained model on ImageNet?
Can you provide the pretrained model?

About the experiment on Meta-LSTM

Hi,Thanks for your great work here!
I wonder if you have the code for Meta-LSTM,and can you share it with me.
Hope to receive your reply,thanks.

What's the TestDataset?

Hi, thanks for your great job! I have a problem when reading the code, that is how should we save the best model during training? And I found that you save the best model by evaluating the model in the testdataset, but I didn't find any descripiton about it, can you tell me what it is?
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