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Hi @B1ueber2y@pengsongyou , thanks for the great work! I have two questions regarding your paper:
For video sequence supervised reconstruction, you mentioned that you did not use masks. Then why does the final predicted shape only contain foreground objects? I assume that the shape should be random at the beginning and the photometric loss is applied to each pixel of a pair of groundtruth images.
It seems that you always optimize the latent code instead of the model. To my understanding, this means for every new object you would need a specific optimization. Is there any reason why you didn't optimize the model and use an image encoder to make the sdf network conditioned on an input?
Thank you!
The text was updated successfully, but these errors were encountered:
Hi @B1ueber2y @pengsongyou , thanks for the great work! I have two questions regarding your paper:
Thank you!
The text was updated successfully, but these errors were encountered: