Closed valentin-fngr closed 1 year ago
Hi, could you please provide more information (model, config, window size) for the results? It seems like fig 1,2,3 are not from the same model (1,2 root fixed, 3 not).
Intuitively, a longer clip length would give better results, which is also verified on Human 3.6M.
Hi, could you please provide more information (model, config, window size) for the results? It seems like fig 1,2,3 are not from the same model (1,2 root fixed, 3 not).
Hi, thanks for your reply. You are right, GIF 1 and 2 are coming from the same "setup" while GIF 3 has been predicted with another training setup. Unfortunately, I do not remember the modification I did. Let me investigate and get back to you.
Is there any reason GIF 1 and 2 would have a fixed root and not 3 ?
Hi, could you please provide more information (model, config, window size) for the results? It seems like fig 1,2,3 are not from the same model (1,2 root fixed, 3 not).
Hi, thanks for your reply. You are right, GIF 1 and 2 are coming from the same "setup" while GIF 3 has been predicted with another training setup. Unfortunately, I do not remember the modification I did. Let me investigate and get back to you.
Is there any reason GIF 1 and 2 would have a fixed root and not 3 ?
It's related to the rootrel
flag in configs.
Hi,
Did you update the pose3D weights for the global_lite model recently ? I had two version of this repo, one older one more recent.
I had to copy the weights from the old repo to the new one to make it work on short clips :
Important note : I have tried the two weights with the same alphapose-results.json to make sure I am testing in the same conditions for both weights.
No it has not been changed.Best,WentaoSent from my iPhoneOn 2 Jul 2023, at 06:43, valentin-fngr @.***> wrote: Hi, Did you update the pose3D weights for the global_lite model recently ? I had two version of this repo, one older one more recent. I had to copy the weights from the old repo to the new one to make it work on short clips :
Important note : I have tried the two weights with the same alphapose-results.json to make sure I am testing in the same conditions for both weights.
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Hi,
Here are some 3D skeletons I extracted from sport clips (tennis).
Tennis back hand :
A longer tennis sequence :
3D representation out of an 8 min vieos
I have noticed that the longer the sequence, the better the 3D pose estimation is. I have also noticed that for a same clip, the angle of the 3D visualization changes with respect to the clip length.
I observe some jittering for very short clips. If you guys have any idea how I can reduce that effect, please let me know.
I have a script extracting the 2D skeleton using AlphaPose and then generating the 3D poses. My 2D pose estimation is very good, but I still get this jittering effect.