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Hi, thanks for your excellent work.But when I use your DAT model and pre trained weights for image segmentation tasks, the effect is not ideal. I do this: take out the features of each layer and then recover the image size through simple deconvolution up sampling and skip connection operations. The code is as follows:
If possible, please tell me where the error is. I hope you can publish the segmentation model as soon as possible and look forward to your reply. Thank you
The text was updated successfully, but these errors were encountered:
The deconvolution is a rather weak operator as the decoder in segmentation models. In fact, it is better to use some powerful decoder heads for segmentation tasks. The detection and segmentation codes are released, along with the extended version of the paper DAT++. We welcome you to check them out. Please feel free to let us know if you encounter any problem.
Hi, thanks for your excellent work.But when I use your DAT model and pre trained weights for image segmentation tasks, the effect is not ideal. I do this: take out the features of each layer and then recover the image size through simple deconvolution up sampling and skip connection operations. The code is as follows:
If possible, please tell me where the error is. I hope you can publish the segmentation model as soon as possible and look forward to your reply. Thank you
The text was updated successfully, but these errors were encountered: