[Question] Could I use DIST in RetinaFace? about image_classification_sota HOT 5 CLOSED

Right. There are two loss terms in DIST, i.e., intra-class and inter-class losses. For inter-class loss, the information is limited with only two categories. For intra-class loss, it could still be effective since it transfers the relations among batch axis.

You could still try DIST on your task, as it is easy to implement. For simple task that is easy to converge, it is recommended to use a larger SoftMax temperature (e.g., T=4 in CIFAR-100), and the performance would be much better than the original T=1.

from image_classification_sota.

Thank you for the great response.

from image_classification_sota.

Sorry but I have one more question.

could it be used in bbox or landmark regression rather than class classification?

from image_classification_sota.

Sorry but I have one more question.

could it be used in bbox or landmark regression rather than class classification?

DIST relax the absolute approximation into relative approximation. However, the regression task requires absolute approximation. So I think it is unsuitable to use (at least only use) DIST in regression task.

from image_classification_sota.

Thank you for the great response.

from image_classification_sota.