title: SLAM system that uses deep learned features?
body: <p>Has anybody tried developing a SLAM system that uses deep learned features instead of the classical <code>AKAZE/ORB/SURF</code> features? </p>
  
  <p>Scanning recent Computer Vision conferences, there seem to be quite a few reports of successful usage of neural nets to extract features and descriptors, and benchmarks indicate that they may be more robust than their classical computer vision equivalent. I suspect that extraction speed is an issue, but assuming one has a decent GPU (e.g. NVidia 1050), is it even feasible to build a real-time SLAM system running say at 30FPS on 640x480 grayscale images with deep-learned features?</p>