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c-he / NeMF

[NeurIPS 2022] Official implementation of "NeMF: Neural Motion Fields for Kinematic Animation"
MIT License
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Clarification on sparse keyframe in-betweening #16

Closed setarehc closed 11 months ago

setarehc commented 1 year ago

Hi, Thanks for this great work and your codebase! In the sparse keyframe setting of the inbetweening experiments (refering to Table 5 in the paper), how are keyframes exactly selected? Do you select the first frame and then, select the next frame every t = {5, 10, 15, 20} frames? This way, when t = 5 and motion length is some arbitrary length, the mask will look like this: [1,0,0,0,0,1,0,0,0,0,1,...] I'm asking this as I'm trying to compare my own inbetweening model with yours and I want to make sure I'm exactly replicating your setup. Thanks :)

c-he commented 1 year ago

Hi, thanks for your interest in our work! You can find the keyframe selection code in our application.py:

https://github.com/c-he/NeMF/blob/79918430970fd138ae730510459c8f34893a3f86/src/application.py#L440-L442

We fix the first and last frames as they are required for SLERP, and the rest of the keyframes are sampled every $t$ frames.