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Hi, thanks for open sourcing your great work! These are really impressive results you showed.
I couldn’t find the data pipeline for T2V in the current code so I was hoping I could ask a question here.
How did you manage the different frame rates across videos (24 fps, 30 fps, 60 fps) in the WebVid dataset? If you just work with frames, the videos will have different time scales — will that affect training? Did you do anything to normalize the frame rate as a preprocessing step, or did the model take the frame rate as a conditioning input?
Thanks in advance.
The text was updated successfully, but these errors were encountered:
Hi, thanks for open sourcing your great work! These are really impressive results you showed.
I couldn’t find the data pipeline for T2V in the current code so I was hoping I could ask a question here.
How did you manage the different frame rates across videos (24 fps, 30 fps, 60 fps) in the WebVid dataset? If you just work with frames, the videos will have different time scales — will that affect training? Did you do anything to normalize the frame rate as a preprocessing step, or did the model take the frame rate as a conditioning input?
Thanks in advance.
The text was updated successfully, but these errors were encountered: