Computer vision summit CVPR has just (virtually) taken place, and like other CV-focused conferences, there are quite a few interesting papers. More than I could possibly write up individually, in fact, so I’ve collected the most promising ones from major companies here.
Facebook, Google, Amazon and Microsoft all shared papers at the conference — and others too, I’m sure — but I’m sticking to the big hitters for this column. (If you’re interested in the papers deemed most meritorious by attendees and judges, the nominees and awards are listed here.)
Redmond has the most interesting papers this year, in my opinion, because they cover several nonobvious real-life needs.
One is documenting that shoebox we or perhaps our parents filled with old 3x5s and other film photos. Of course there are services that help with this already, but if photos are creased, torn, or otherwise damaged, you generally just get a high-resolution scan of that damage. Microsoft has created a system to automatically repair such photos, and the results look mighty good.
The problem is as much identifying the types of degradation a photo suffers from as it is fixing them. The solution is simple, write the authors: “We propose a novel triplet domain translation network by leveraging real photos along with massive synthetic image pairs.” Amazing no one tried it before!