As I understood, the TSD fine tunes proposals from the RPNs existing in Faster RCNN, Mask RCNN, Cascada RCNN etc.
In RetinaNet we don't have region proposals but instead the head convolves the different levels of the FPN using anchors.
Theoretically, what if a certain spatial convolution location is good for the classification but a slightly offset one is better for regression, just like in the TSD case?
Wouldn't RetinaNet benefit from a TSD head as well?
As I understood, the TSD fine tunes proposals from the RPNs existing in Faster RCNN, Mask RCNN, Cascada RCNN etc.
In RetinaNet we don't have region proposals but instead the head convolves the different levels of the FPN using anchors.
Theoretically, what if a certain spatial convolution location is good for the classification but a slightly offset one is better for regression, just like in the TSD case?
Wouldn't RetinaNet benefit from a TSD head as well?