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Someone asked about
> I'm currently trying to use your "Speech Representation Disentanglement with Adversarial Mutual Information Learning for One-shot Voice Conversion" repository to train a VC …
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using my own video, I got some results. Most of the outputs seems good, but there are still some questions.
- In common sense, the action of eye close should not have an effect on the other region of…
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Hi authors, i have been trying to reproduce the results but not been able to reproduce them, can you provide me the exact hyper parameters used for training, and number of epoch you trained to produce…
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Hello,
The Camelyon17 ERM results in Table 4 seem exceedingly high compared to other papers that used the same setup (i.e., ResNet-50 pretrained on ImageNet), e.g.:
1. "*Improving Multi-Domain Gen…
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Are you solving the following problem? If not, we can discuss it.
Disentanglement Failures. For Churches, the background sometimes contains a church, and for CompCars, the
object sometimes contain…
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I'm not happy with the results of the large sweep that we ran on LINCS. Mainly:
- We should fix the latent space dimension to 64 (or 32?). This also restricts the number of parameters for the Vanilla…
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I wanted to pair the TC and Ldis described in your paper with the tc_loss in your code. I felt confused about the discriminator in your code. Why does the output of the discriminator have two dim? Fur…
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Hello @ryoungj,
first of all, thank you for sharing your code! This is an amazing work!
I read your paper and I would start to replicate the results that you reported in Table 1.
In particular…