Comments (3)
Hello @hathawayxxh !
I don't think we have the visualization code in this repo, but you can find a more recent one (utilizing hyperboli UMAP algorithm) in our hyperbolic metric learning repo
from hyperbolic-image-embeddings.
Hi Valentin,
Thanks for your reply. I have checked the repo that you provided, which is not the visualization effect as I thought. For the Fig. 1 of "Hyperbolic Image Embeddings", some of the pictures of the data points are illustrated in the poincare ball. Is that drawn by codes or manually?
Best,
Xiaohan
from hyperbolic-image-embeddings.
Hi Valentin,
Thanks for your reply. I have checked the repo that you provided, which is not the visualization effect as I thought. For the Fig. 1 of "Hyperbolic Image Embeddings", some of the pictures of the data points are illustrated in the poincare ball. Is that drawn by codes or manually?
Best, Xiaohan
Hi, hathawayxxh. Do you figure out how to draw the Figure1 and visualization? If so, can you kindly help me and provide some advices?
from hyperbolic-image-embeddings.
Related Issues (14)
- A typo on the main plot and poincare_mean implementation HOT 1
- Code to calculate the hyperbolicity of image datasets HOT 3
- Is it necessary to use Riemannian optimzers?
- Calculating Hyperbolicity bug in delta.py? HOT 1
- mnist example get loss nan HOT 5
- is it a bug in HyperbolicMLR?
- Can't achieve the accuracy as reported in the paper. HOT 2
- Reported results and reproduced results HOT 12
- Poincare distance to origin HOT 3
- Hyperbolic CNN HOT 2
- Reproducing Results
- could you release the code for reid๏ผ
- The values of '_mobius_add(-x, y, c).norm(dim=-1, p=2, keepdim=keepdim)' are ones HOT 2
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