Comments (3)
DanChen001
commented on July 18, 2024
@wk910930 @unsky I have the same question. Could you help me? Thanks
from deformable-convnets-caffe.
wk910930
commented on July 18, 2024
Unfortunately, I didn't get the answer from the author yet. I guess deformable_group allows for more possibilities. When deformable_group is set to 1, the same predicted offset will be applied to all the 3 x 3 filter inside a kernel volume. When deformable_group is set to, say 4, the filters will be divided into 4 groups and each group has its own offset to apply. This operation may produce better results (because of varied offsets).
from deformable-convnets-caffe.
DanChen001
commented on July 18, 2024
Unfortunately, I didn't get the answer from the author yet. I guess
deformable_groupallows for more possibilities. Whendeformable_groupis set to 1, the same predicted offset will be applied to all the3 x 3filter inside a kernel volume. Whendeformable_groupis set to, say 4, the filters will be divided into 4 groups and each group has its own offset to apply. This operation may produce better results (because of varied offsets).
@wk910930 Thank you for your kind help.
from deformable-convnets-caffe.
Related Issues (20)
- the error after make HOT 4
- could you release deformable roipooling HOT 2
- Ask for help ，about the traing of deform HOT 3
- The hyper-parameters for reproduce the deform conv model on VOC
- About example 'mnist' HOT 2
- model share
- ResNet50_dcn_iter_30000.caffemodel
- matcaffe error HOT 7
- caffemodel HOT 2
- train.prototxt
- shape mismatch HOT 1
- Have you ever tried deformable conv on classification network？ HOT 2
- Serious problems occurred when training cls network with dcn HOT 2
- Problem about the code. HOT 5
- Use by pycaffe
- 有两个bug
- Does anyone solve the problem of over large offset?
- Shape of bottom[1]
- Can you provide one train.prototxt with deformable ROI pooling?
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