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Yes, we just use 'u v' as the condition in the frame-based experiment, which is strong enough.
The feature from the context encoder is mainly used for video-based experiments which require dense spatial-temporal information.
When we have time in recent months, we will update the model for the video-based pipeline. Thanks :)
Yes, we just use 'u v' as the condition in the frame-based experiment, which is strong enough. The feature from the context encoder is mainly used for video-based experiments which require dense spatial-temporal information.
When we have time in recent months, we will update the model for the video-based pipeline. Thanks :)
Hello,does ‘GCNpose’ just get the 3D pose directly?
In the paper a 'Context Encoder' is used to condition the diffusion model.
It appears that this conditioning is here https://github.com/GONGJIA0208/Diffpose/blob/main/models/gcndiff.py#L101 but doesn't appear to be used. Is this the case?
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