Edit: looks like the Dirac video codec is based on wavelets. Good to know all of that research wasn’t for nothing!
It's not as hyped as mainstream deep learning methods but I think it holds a lot of promise since it cuts down on learning time, is mostly unsupervised, gives you control over the network's features and is a more theoretically principled way to build networks than just defining the loss and crossing your fingers while it's optimizing as we're doing right now (bit of an hyperbole).
I could go on, it's absolutely fascinating. More info (in english & french): https://edouardoyallon.github.io/thesis.pdf
On the more general area Mallat has a good and approachable (not very technical) book on the area: "A Wavelet Tour of Signal Processing". Worth a look for anyone intrigued by wavelets.
Wavelet-based codecs turned out to be much harder to implement in hardware that fourier-transform-based ones (for which we have FFT!). That disincentivized development, which is why you only have Dirac (an open-source, non-HW-industry-backed effort) that uses it.
[0] http://www.darktable.org/2011/11/darktable-and-research/
Are we talking about roughly the same encoding time, or the DWT is slower by an order of magnitude?