Comments (3)
- We reduce the stride to increase the output resolution. This results in a decrease in receptive field which is mitigated by dilated convolution. This is a standard practice in segmentation networks.
CascadePSP/models/psp/extractors.py
Line 28 in 3e9a79b
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Thanks. May I ask the reason why the padding parameter in step_size = stride - padding * 2
is set as 16?
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It is empirically set. With a larger padding it should also work; with a smaller padding you might run into boundary artifacts.
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Related Issues (20)
- Error while running demo code!! HOT 4
- How to change epoch? HOT 3
- Segmentation Refinement Runtime Error HOT 11
- Train the Net HOT 4
- How to implement 'Local step' only? HOT 2
- how to solve this problem? HOT 2
- refinement is not a binary image HOT 1
- Can this method be used as post-processing for video object segmentation? HOT 2
- local step only HOT 4
- Help with Colab/local setup HOT 3
- Tree leaves boundary refinement HOT 5
- hashlib error HOT 1
- weight coefficient
- Very slow prediction, high cpu /gpu usage HOT 1
- Car Window Refinement
- Whether this model can be applied to Cityscapes datasets? HOT 1
- How to train PSPNet/DeepLabV3+ just as the result in your paper HOT 12
- Any low hanging fruit for generation speed improvements? HOT 2
- About the problem of dealing with redundant incomplete masks HOT 2
- Query Regarding High-Resolution Image Segmentation with CascadePSP HOT 1
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