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Hi,thanks for sharing the code,after reading the code,I wonder why you add dcn and stage_with_dcn to image backbone config, and use mask-rcnn trained in nuimage which config don't have dcn, and why you add other fpn layer to process_detector_feat, as I see in paper figure 2, you don't plot the fpn layer.
The text was updated successfully, but these errors were encountered:
The normal convolution can replaced with the deformable convolution seamlessly thanks to the 'zero init' property of the deformable offsets.
There is actually 1 fpn layer in process_detector_feat, which works as a convolutional layer.
Hi,thanks for sharing the code,after reading the code,I wonder why you add dcn and stage_with_dcn to image backbone config, and use mask-rcnn trained in nuimage which config don't have dcn, and why you add other fpn layer to process_detector_feat, as I see in paper figure 2, you don't plot the fpn layer.
The text was updated successfully, but these errors were encountered: