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AliaksandrSiarohin avatar AliaksandrSiarohin commented on June 22, 2024

We did not include vox, because there is no benifit in using current model. As explained in the paper. The checkpoint and config for vox is still provided.

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yaseryacoob avatar yaseryacoob commented on June 22, 2024

Since you actually went through effort of evaluating it, even if it didn't improve, there are insights that can develop from the new framework on such data. Your work so it is your call. Thanks for responding.

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ChengBinJin avatar ChengBinJin commented on June 22, 2024

We did not include vox, because there is no benifit in using current model. As explained in the paper. The checkpoint and config for vox is still provided.

@AliaksandrSiarohin
We evaluated the vox256.pth that provided in this repository on our own face-related test set. The quantitative result shows that this model is better than the vox-adv-cpk from FOMM.
Can you speculate on the reason why the model results become better?

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AliaksandrSiarohin avatar AliaksandrSiarohin commented on June 22, 2024

Just a speculation. This model has better generalisation when estimating affine transformations, you can see explanation for this phenomenon in the toy experiment section. Because we evaluate model on faces we did not observe an improvement, since vox dataset is already large and generalisation is not a problem. Since your dataset is face-like, generalization may still be the issue.

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ChengBinJin avatar ChengBinJin commented on June 22, 2024

Thank you for your explanation! I really like your this work, and MonKeyNet and FOMM too.

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