Closed zay1817 closed 1 month ago
We guess that is because the rank contrastive iteratively forces most of the samples to have lower values. We thought that having negative values is not much a problem since highlight detection aims to capture the frames with relatively higher saliency scores. So normalizing the per instance value is an easy way to convert negatives into positive values.
Thanks for your reply.
May I ask why the result of my training ”pred_saliency_scores“ is always negative?