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The context images used in the model seem to have the same intrinsic during the training process. Do your pre-trained weights support inputting two images with different intrinsics for training or inference? If not, do I need to retrain the model?
Thank you in advance for your time!
The text was updated successfully, but these errors were encountered:
Hello, thank you for your insightful question. We train directly with re10k and dl3dv, so all image pairs have the same intrinsics. I have not tested the case where the input image pairs have different intrinsics, but I think retraining on data with different intrinsics gives better performance. If you have any results and would like to share them, that would be great.
Thanks for your explanation. Based on my tests, the current pre-trained model doesn't support different intrinsics. Therefore, it needs to be retrained on data with different intrinsics.
The context images used in the model seem to have the same intrinsic during the training process. Do your pre-trained weights support inputting two images with different intrinsics for training or inference? If not, do I need to retrain the model?
Thank you in advance for your time!
The text was updated successfully, but these errors were encountered: