Update: I have some code available. Gaussian blur now implemented as a F.conv2d op on pytorch tensor. Adopt this for your use case.
I found this a useful data augmentation esp. if your dataset comes from out of focus end user photos. This is even more frequent if you are making inferences continuously from a video stream. I find Gaussian Blur + Shear is also a good approximation for motion blur.
It is actually hard to curate naturally occurring out of focus or motion blurred photos because user usually don’t post them. Lot of benchmark and competition actually use clear photo (even in low resolution) so the need for this is less there as an open src library. But I do suspect companies implement this internally to deal with the scenario I mentioned.
Would like to hear feedback, and if you have experience with this.