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It is impressive given current state-of-art. Your summary doesn't seem fair. Take a look at the first set (Set5) [1], and set upsampling scale to 4x and flip be
by dmos62 10y ago
It is impressive given current state-of-art. Your summary doesn't seem fair. Take a look at the first set (Set5) [1], and set upsampling scale to 4x and flip between Bicubic and LapSRN. What seems most exciting to me, is that LapSRN is more resource efficient than bicubic.
[1] http://vllab1.ucmerced.edu/~wlai24/LapSRN/results/Set5/ http://vllab1.ucmerced.edu/~wlai24/LapSRN/results/Set5/
- x1798DE 10y agoWhether or not their sampling is impressive given the current state of the art (though in that same set the other, non-bicubic methods seem to do pretty well compared to LapSRN), that gif definitely seems misleading. It's not obvious at all what is happening here, and it doesn't really even show off their method very well (as, say, separate gifs for each of the downsampling rates and/or clearly labeled frames). The way it is now, it really seems like each progressive enhancement is another stage in the image reconstruction.
- dmos62 10y agoThe banner gif is confusing, reminds me of the Super Troopers Enhance scene. Not fitting for an academic publication.
- thanatropism 10y agoI remember a proprietary image format (complete with a proprietary converter and viewer for Windows) in the 1990s that dubbed itself a "fractal compression algorithm" -- and did an impressive job with things like water ripples in rivers or grassy terrain. You could "zoom in" 8-10X in an original nature photograph and be semi-convinced.
- vernie 10y agoIt's still around: https://en.wikipedia.org/wiki/Genuine_Fractals https://en.wikipedia.org/wiki/Genuine_Fractals