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eeng_ t1_iy82r1q wrote

This is probably obvious to you, but most of the frames in a long video are redundant and provide little additional information. You could easily extract some key frames (eg substract previous frame from current frame and apply a fixed threshold), then run your network only on key frames and then ensemble these key frame predictions into a single label per video.

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Vae94 OP t1_iy8fy1f wrote

Yes. Thanks for sanity check!

I was thinking of first coming up with algorithm to find outliers and the training LSTM only on the outliers, for that I should assemble some meta-algorithm I guess and train both LSTM and trimming network at the same time.

I was wondering if something like this exists in literature already?

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