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>we do not take random pictures of dogs Sure we do. The vast majority of computer vision training images come from self-driving cars’ cameras. None of the stre

>we do not take random pictures of dogs Sure we do. The vast majority of computer vision training images come from self-driving cars’ cameras. None of the streetscapes they capture are deliberately composed, as the portrait of a pet dog might be. Yet models trained on the random streetscapes captured by self-driving cars can easily classify objects, even if they are present merely as random background entities, and not the carefully and consistently framed subject of a photo. >I think it's highly doubtful anything in ML (, modern AI) would work if pointed "open-camera" at arbitary parts of the world. But it does.

gtirloni 3y ago
I believe that's what Google does when it asks you to record your surroundings so it can pinpoint your location. And it works, yes.
hmmSceptical 3y ago
You what? It may be like that on modern captcha mechanisms, but that was not how we got here (I.E "The vast majority of computer vision training images come from self-driving cars’ cameras"). Are you to young to remember when captcha's were based on Googles/others scans of books? For like 10+ years the baseline was "handwritten" digits / "book text" and how well models could identify them... Google spent millions on fighting lawsuits over this... I think you must be young (not that im insulting you, just that im showing my age and im < 30)
mjburgess 3y ago
Computer Vision in cars is trained on supervised data -- ie., human-labelled.
uoaei 3y ago
Cars are usually centered on the road, and the built environment has certain regular features that induce structure in the dataset of images. The same insight applies there too and GP's argument stands. Dogs don't often float upside down above treetops, for instance.
bastawhiz 3y ago
> computer vision training images come from self-driving cars’ cameras Isn't this just another way of saying "we put cameras in human environments pointing at semantically relevant things"? Self driving cars aren't looking at rooftops or the inside of drains or straight down from high up. They're positioned where people are often looking from at things in human environments. Dogs, to use that example, are implicitly the subjects. We care deeply that self driving cars can see and recognize dogs (or one would hope). If self driving cars had cameras mounted randomly at various angles and the cars drove without direction off-road wherever they pleased and took off like a drone to observe from the sky, you can be assured dogs would not be easily recognizable without supervision.

gtirloni 3y ago

I believe that's what Google does when it asks you to record your surroundings so it can pinpoint your location. And it works, yes.

hmmSceptical 3y ago

You what? It may be like that on modern captcha mechanisms, but that was not how we got here (I.E "The vast majority of computer vision training images come from self-driving cars’ cameras"). Are you to young to remember when captcha's were based on Googles/others scans of books? For like 10+ years the baseline was "handwritten" digits / "book text" and how well models could identify them... Google spent millions on fighting lawsuits over this... I think you must be young (not that im insulting you, just that im showing my age and im < 30)

mjburgess 3y ago

Computer Vision in cars is trained on supervised data -- ie., human-labelled.

uoaei 3y ago

Cars are usually centered on the road, and the built environment has certain regular features that induce structure in the dataset of images. The same insight applies there too and GP's argument stands. Dogs don't often float upside down above treetops, for instance.

bastawhiz 3y ago

> computer vision training images come from self-driving cars’ cameras Isn't this just another way of saying "we put cameras in human environments pointing at semantically relevant things"? Self driving cars aren't looking at rooftops or the inside of drains or straight down from high up. They're positioned where people are often looking from at things in human environments. Dogs, to use that example, are implicitly the subjects. We care deeply that self driving cars can see and recognize dogs (or one would hope). If self driving cars had cameras mounted randomly at various angles and the cars drove without direction off-road wherever they pleased and took off like a drone to observe from the sky, you can be assured dogs would not be easily recognizable without supervision.