Comments (4)
Thanks for your interest in our work. The seed cues which stored in the pickle file is very important. In every training iteration, the current supervision grows starting from the original seed cues rather than the last iteration generated seeds. And you can find the sentence "To ensure the stability of training, DSRG always chooses the original seed cues as initial seed points" in our introduction section. In a word, we do not perform the seeded region growing with the previous seeds.
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Thanks for your clear explaination. So the bottom row results in Figure 1 whether can be understood as for a certain input image, in every epoch, although a same cues pickle file is always loaded as the initial seed , the label map can still dynamic updating because of the constantly changed CAM during training?
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The label map can still dynamic update because of the constantly changed segmentation networks during training. We use the CAM to generate the initial seed (cues pickle file) offline. Afterward, we have not used it.
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OK, I see. thank you very much. (It's my fault, the "CAM" I just said is the probability map "fc8-SEC-Softmax" in the code)
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Related Issues (20)
- Do you add val split data for training when report results on test split HOT 2
- About Seed with person HOT 6
- Comprehension of pretrained VGG16 model HOT 3
- questions about seed-loss
- About Loss Function HOT 1
- A juvenil question
- Training with custom data
- Failed to load caffe layers
- Loss calculation is too slow HOT 2
- Understanding Seeding Loss
- Understanding the data in `localization-cues.pickle` file HOT 3
- I can't run 'pip install CRF/'.
- about vgg16_20M_mc.caffemodel
- Localization cues HOT 3
- How to generate localization-cues.pickle file using personal dataset, voc style? HOT 1
- what image size has been used for the final segmentation training?
- resnet weights initialized from ImageNet? HOT 2
- Reproducing Paper Results HOT 7
- comprehension of DSRG HOT 2
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