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Is TCN suitable for spatio-temporal data? #73
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I have a similar question. I want to use a TCN for video data. Anyone have any ideas? |
I have found a solution using an encoder. |
I was wondering if you could share the solution? Thanks, |
Did you find a solution? |
Just use any encoder and set channels to the output dim for one time step of the encoder. For example if you have some CNN model that inputs image (n_imgs,112,112) and outputs (n_imgs, channels), you simply input that into a CNN making sure that n_channels = channels and n_imgs is the length not the channels (possibly requiring reshaping). Lmk if that makes sense. |
You are correct in saying that we can use any CNN backbone initially to transform the input images (n_imgs, W, H, C) into (n_imgs, W', H', C'), where W', H', and C' are derived from the last feature map. To reduce the dimensions of W and H, we can employ either flattening or global average pooling (which is recommended) so that the dimension becomes (n_imgs, C'). Afterward, we can feed the transformed data into TCN. Please let me know if you need any further clarification. |
How does it perform?
How does it perform? |
I have dimensional spatio-temporal data which the spatial part is represented by 2D matrices(like an RGB image). How can I feed the data to the TCN?
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