Closed IanYeung closed 4 years ago
Yes, the features from the deconv_3 in line 76 are aligned features. To further enhance transformation capacity and explore more contexture information for reconstructing the target aligned pixels (the predicted offsets will flexibly enlarge receptive field), we use additional regular deformable convolution layers (not for temporal alignment as the layer: deconv_3).
Thanks for your quick response.
https://github.com/YapengTian/TDAN_VSR/blob/c00b8d15f91fbf652102c9fd21c247cdfdbe6e21/model.py#L76-L78
Isn't it the feature aligned in line 76? Why you need to further pass through another deformable convolution layer in line 78?