When you dig into the paper, this is not quite the case. The system actually only uses 5312 landmarks (off by a factor of 10), and they only evaluate with 963 of these. They test 728 landmark images from 124 landmarks, and it correctly identifies 337 (46%) of the landmark images. It also correctly guessed that 417 are landmarks of some sort (e.g. that the Eiffel tower is “a landmark”). The 80% number comes from the fact that of the items that were classified as “landmarks”, it correctly identified which landmark it was (337/417).

That’s a very interesting interpretation of accuracy: if it misses something completely, no problem, doesn’t count It’s kind of like a student taking an exam and saying “I didn’t answer questions 6-10, so you can’t count them!”

I believe the more accurate statement would be:

“…efficiently identify images of 124 landmarks (out of 963) from all over the world with 46% accuracy”

But, hey, that’s a tougher sell.

You won’t find free new algorithms from Google genuinely or openly being made freely available like the way that Microsoft does. I frequently request papers from Google researchers, but that’s because I stumbled upon their work from the online literatures (where only the abstracts that are available for viewing but not the full publication).

I regularly check out the Microsoft Research’s various groups publications just to check if any new algorithm would be of interest to me. I had implemented various algorithms being published in Microsoft papers (mostly from Web Search & Mining) in the past and they (authors) were eager to help me out, in giving more details about methods of implementations (faster versus accuracy), checking my codes for correctness, memory issues, etc,…

Text-Search Tricks Speak Volumes in Image Search

There are lots of various research topics that are pouring out of Microsoft Research Asia Division over the last few years which are being published in the computing literatures where Google and others might be close or secretive about their R&Ds although they do occasionally publish their researches, one can always find that Microsoft is ahead in cutting-edge new researches. Since Google doesn’t publish as many research articles as Microsoft and when something or product comes out of Google, you thought, umm, Microsoft’s R&D people have been doing development in that area before Google had jumped in.

i mean, sure, you could probably name half a dozen narrow use cases, but when you add it up i doubt any of them rise to the level of being something people would pay for.

i imagine the most important use for it will be in image search. but photos of monuments are already pretty easy to come by. and honestly, once you’ve seen 2 or 3 pictures of a monument, you’ve seen them all.

I find this assessment a little bit self-sufficient… is matching a few keywords “unlocking the information stored in text” ???

there is none for landmarks yet.

A more likely impediment to commercialization is the huge number of photos, the limited number of landmarks and computational expense of adding more.