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Question about Motion Supervision and Point Tracking
Hello,
Thanks for sharing your great work!
I have 2 questions regarding motion supervision:
- Why do you normalize the direction vector $d_i$ in the loss (equation 3)? Can't we directly optimize for matching the position $g_i$ itself? Is it for making the latent optimization more gradual? If so, how important is it?
- Maybe related to the previous question -- why is the point tracking step necessary? I see that in equation 3 you are taking the target feature $sg(F_q(\hat{z}^k_t))$ from the optimized latent, which of course requires $q$ to be updated in the next steps by point tracking. But why can't the target feature be taken from the original latent, without having to update $q$?