Comments (5)
We apply CRF as the post-processing in testing. The predicted map after CRF is a binary map. You can find the link of the code in README/Test.
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I downloaded your result maps, and found that there are still some pixel values between 0~255, e.g. 624.jpg. So I can't get the same accuracy and BER value as listed in your paper. Can you share the evaluation code?
In fig.5 of your paper, the last three columns also seem like intensity maps.
Thanks for your quick reply.
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Maybe some images I forgot to apply the CRF. Anyway, the results should be similar. Please give me your email and I send you the evaluation code.
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[email protected]
thanks very much
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Dear Xiaowei,
I am interested in your work. I test your results but found the results have some difference in your paper, could you share the evaluation code with me for better evaluation?
My email is [email protected]
Thanks very much
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Related Issues (20)
- Out of Memory Error HOT 1
- Test file error HOT 1
- Error in Running the Testing Code in Matlab as well python HOT 1
- Shadow removal results without the pre-trained filters HOT 3
- loss is so big HOT 1
- NO model named DSC_iter_160000_lab.caffemodel is found HOT 1
- 求助! HOT 3
- irnn-layer missing HOT 2
- Which part reflect 'Direction-aware attention mechanism' in the code? HOT 1
- During running DSC_test.ipynb, "caffe.LayerParameter" has no field named "irnn_param". HOT 4
- 训练报错
- loss Function HOT 1
- What is the running speed of the model? HOT 1
- Where can I find UCF dataset? HOT 3
- 配置好caffe之后,在跑detection.m程序的时候,matlab闪退
- 模型求助
- About the shadow removal evaluation of SRD dataset
- The size of the test set on SRD is 405?Shouldn't it be 408?
- BER和accuracy
- 请问removal部分有torch版本的吗?
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