Comments (2)
Hello, @pigcv
Thanks for your interest.
We conducted an experiment for comparing the performance of pseudo-masks. We also observed the performance when applying dCRF. We tested various CRF hyper-parameters based on the previous papers and chose them with the best performance. We referred to the official code/paper of DeepLab, PSA(https://github.com/jiwoon-ahn/psa), and OAA.
The difference in the performance according to the hyper-parameters among the papers is not that big, but not negligible.
Finally, we chose the hyper-parameters of DeepLab-V2 (ResNet101-based) for dCRF in the experiments. Please see the website of DeepLabV2 for them. By the way, the hyper-parameters are different according to the backbone network in the official DeepLab code.
If you have any question, please leave an issue here :)
Thanks!
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Thanks for your reply~
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Related Issues (14)
- Where is the codeοΌπ HOT 1
- DeepLab setting HOT 3
- COCO segmentation code HOT 3
- Performance of VGG16 based Deeplab-v1 HOT 2
- Train EPS on other dataset. HOT 3
- About the color map of coco 2014 HOT 1
- The coco performance 37.15 is just the performance of the pseudo mask? HOT 1
- What is the novelty of your paper? HOT 8
- Deeplab-v2 pretrain model HOT 4
- COCO training codes HOT 5
- COCO training codes too. HOT 2
- COCO checkpoint HOT 1
- Regarding portnig the code to google colab HOT 1
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