Comments (4)
I think you may refer to the https://github.com/Finspire13/pytorch-i3d-feature-extraction repo for details. They add an average pooling operation to turn the [N, C, T, H, W] feature into [N, C] features. Thus, each clip will become a single tensor with [C] shape, and all clips (suppose we have M clips) in a video will become a feature sequence like [M, C].
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We use features from I3D after the last average pooling, resulting in a single feature vector of size C for each clip and thus a sequence of features (T x C) for each video. My bet is that the I3D features you have extracted are before the average pooling and thus preserve the spatial dimension.
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Let me know if there is any further questions. Otherwise, I will mark the issue as resolved.
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Mark as resolved.
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