[alleycat5000]

There's a good paper on this:

https://demuc.de/papers/schoenberger2017comparative.pdf

"Our evaluation confirms that, as expected, learned descriptors often surpass SIFT on all evaluation metrics. However, we also observe that advanced versions of hand-crafted descriptors perform on par or better than the state-of-the-art learned feature descriptors, especially in the more complex SFM scenarios. As such, our paper demonstrates that there is still significant room for improvement for learning more powerful feature descriptors."

[Rochetshipz]

This paper is a bit "old" by the way. An excellent paper was released a week ago : https://arxiv.org/abs/2003.01587

Findings are mostly the same. For day/day images, with a properly tuned pipeline, SIFT is really good.