[gcr]

Yup yup! This was the screenscraping technique we used to turn Facebook into an automatic face detector: https://arxiv.org/abs/1602.04504

It's a giant pain to screenscrape this using 'curl'. If I recall correctly, the bounding box coordinates I wanted are set as CSS properties inside inline HTML sent to the client wrapped up in a Javascript string literal as part of Javascript served to the client as the result of an AJAX call, if memory serves correctly. To get my screenscraper working, I had to do the AJAX call, parse the literal javascript, walk the AST to find the string literal I needed, parse the HTML to find the element I needed, then use the computed CSS properties. Looks like the author of this post found a much nicer way.

(note: that work wasn't about recognition; it was about just finding the faces in images, not identifying them)

[tedmiston]

I'd really like to read your paper. Everywhere I've found it referenced has a paywall. Is the full text freely available anywhere?

[jey]

Click "PDF" on the right side and you get https://arxiv.org/pdf/1602.04504v1.pdf

[sillysaurus3]

There's a little-known way to solve that problem for any paper: post the link to /r/scholar, and you'll get the full pdf within a couple hours.

[mablap]

I wouldn't call it 'little-known', it's become quite "famous" in my academic circles at least.

Just make sure you look up the DOI on libgen.

[fapjacks]

Sci-hub doesn't have it?

[anewhnaccount]

That's a link to arXiv which the biggest publicly available preprint server. That means you can get it for free legally.

[danielmorozoff]

Have you quantified the number of people per account that FB is giving a suggested label to a detected face vs a users number of friends? It'd be interesting to see how FBs classifier performs.

[gcr]

Hm. I haven't quantified that, no. I think FB will only suggest labels that it's already very confident of.

[danielmorozoff]

I'd assume the they would be thresholds but the statistics would be interesting.

[bknarendra]

Yes if you see the code, I extract the JSON object from response by removing the for(;;); in the beginning and then parse the json to hash and flatten it to array of strings. As there is only 1 value that will have the html content, I found this by using some css selector of the content and then parse the html and used unique css selector class for the names of the users.