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Epiphqny avatar Epiphqny commented on May 20, 2024

Hi @sally1913105, we compute the spatial and temporal attention, then for 36 frames sequence there are 36 attention weights for each prediction, even the prediction is for a specific frame. In this way, the features from other frames could help the segmentation of this frame.

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sally1913105 avatar sally1913105 commented on May 20, 2024

Thank you for your answer! Can I think of it as within the 36 attention weights of ith prediction only ith attention weights is for ith features and others attention weights is for other features? but How to combine these 36 attention weights?

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Epiphqny avatar Epiphqny commented on May 20, 2024

hi @sally1913105, for each prediction we only use the attention weights of the corresponding frame in this stage. The weights do not need to be combined. Interaction with other frames is realized by the following 3D convolutions.

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