Comments (5)
same question.
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+one
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+1
BTW the work same to 'few shot' leanning that used prototype, Thanks
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@gaowq2017 pls read the paper more carefully.
As we mentioned, our work shows the promise for formulating general segmentation and few-shot in a unified view of prototype learning. Ps: Prototype learning is a quite huge area (what a pity someone directly links it to few-shot learning).
Our work also shows an appealing direction -- the combination of supervised learning and unsupervised, within-class learning (clustering) leads to a more powerful pixel-classification framework.
We will have some more amazing results, let's wait and see.
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@wenguanwang
Thanks for your great work. I am agree that Prototype learning isn't only few-shot learning. I look forward to more similar work, thanks
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Related Issues (20)
- When will the code be released?
- Question regarding IoUs of pretrained HRNet Proto HOT 3
- Question about seed HOT 3
- Layernorm in Prototype learning HOT 1
- Please how to continue training on the previous model, setting --resume_continue y does not take effect
- How long is the speed of each picture in the model test?
- intra-class prototypes is same. HOT 2
- Can't run the code because of dims
- awesome work!
- Question about the existence of the normalization, and how to run it
- Initial Prototype
- Question about the prototype initialization? HOT 2
- 'ce_weight' parameter in loss
- parameter numbers of the entire model? HOT 2
- Questions about code HOT 1
- Question about loss HOT 5
- Question about paper [# model parameter] HOT 6
- Question about Within-Class Online Clustering HOT 8
- Questions about K prototypes HOT 1
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