Comments (1)
You can either upsample the features then compute the distances or compute the distances then upsample them, the upsampling is only done for better visualization, you can even just apply TSNE / PCA over the features to see the clustering of the features
Hope this helps
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Related Issues (20)
- Labels for unsupervised HOT 1
- Cusom dataset with one class HOT 2
- adjusting the model for input images with 4 channels HOT 3
- Training model only on foreground labels HOT 3
- inference with 4-channel model HOT 7
- Adjust the number of decoders HOT 2
- checkerboard HOT 7
- How can I train this model using my own dataset? HOT 1
- About checkpoint HOT 1
- About loss_unsup
- dataloader HOT 1
- Errors while inferencing the trained model HOT 1
- What are the required dimensions of `predict` and `target` for abCE loss? HOT 2
- Program error during training HOT 1
- Training on custom datasets in CCT. HOT 4
- Question about the plot of Figure 2 in the paper HOT 1
- 自定义数据集问题
- Why use MSE instead of CE and KL divergence
- How to perform binary segmentation only ?
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