The use as a pathfinding technique immediately stood out to me. If I'm understanding the way it works it results in variable speed, making it less useful for some game purposes. But this is super useful for animation. If you are trying to model crowd behavior your entities will seemingly speed up and slow down to allow others to pass but still arrive where you need them to at specific times.
One thoughts I had when first I skimmed the paper is that it should be straightforward to train a small, fast DNN to approximate the technique, and then use the DNN for applications that have more stringent performance requirements, including games.
Make sure to watch the short explanatory video (and turn the sound on) -- here's the direct link:
https://www.youtube.com/watch?v=-uXFYpVumh4
The short video is great. The paper looks great (based on a very quick skim; this is an area in which the authors have far more expertise than me). The high-level explanations are great. The web page is great -- informative and to-the-point. Really impressive work!
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EDIT: The senior author is here at https://news.ycombinator.com/item?id=31134139 -- his comment should probably be above mine. Please upvote it.