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Thank you for your nice work!
Since the training code of QueryTrack is not released, I hope you can share the following training details with me:
Thanks again.
The text was updated successfully, but these errors were encountered:
Thank you for your nice work! Since the training code of QueryTrack is not released, I hope you can share the following training details with me: What are the meaning of $\alpha_t$ and $\gamma$ in the formula(7) (the definition of the tracking loss) Is there any document about your contrastive focal loss? Thanks again.
$\alpha_t$ and $\gamma$ is the same as $\alpha$ and $\gamma$ in focal loss.
In form, our contrastive focal loss is a focal loss with softmax function (Eq.5-Eq.7).
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Thank you for your nice work! Since the training code of QueryTrack is not released, I hope you can share the following training details with me: What are the meaning of $\alpha_t$ and $\gamma$ in the formula(7) (the definition of the tracking loss) Is there any document about your contrastive focal loss? Thanks again. $\alpha_t$ and $\gamma$ is the same as $\alpha$ and $\gamma$ in focal loss. In form, our contrastive focal loss is a focal loss with softmax function (Eq.5-Eq.7).
Thank you for your nice work! Since the training code of QueryTrack is not released, I hope you can share the following training details with me:
Thank you! By the way, I have another question. During the calculation of losses['loss_cls'] in class DIIHead, the value of label_weight is always 1:
losses['loss_cls']
label_weights[pos_inds] = pos_weight label_weights[neg_inds] = 1.0
label_weights[pos_inds] = pos_weight
label_weights[neg_inds] = 1.0
However, when calculating avg_factor, only positive samples are included. Could you please tell me why? Thanks a lot!
avg_factor
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Thank you for your nice work!
Since the training code of QueryTrack is not released, I hope you can share the following training details with me:
Thanks again.
The text was updated successfully, but these errors were encountered: