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Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

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Re: Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

#21
post #19

Earlier quoted context omitted.

Nothing would benefit the scientific enterprise more than explicitly publishing papers about failed experiments. How much public money, time, and careers have been wasted chasing something that is already known not to work?

Unfortunately, careers don't get advanced that way. There are very backwards incentives.

I’m aware, I left the academic world in no small part that I refused to write papers that weren’t worth reading. A high quality, but short, CV is a career ender these days. I’m happier now though!

Re: Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

#22
post #11

Can someone explain the meaning of labelled vs unlabelled in this context? What kind of information would the labels carry? Did they have depth maps for all 62 million images or not?

They explain in the paper that they used 1.5 million images with known depth maps (labels) to train a teacher model, and then used the teacher model to create pseudolabels (inferred depth maps) for the full dataset. Then they trained a student model to recover those pseudolabels from distorted versions of the original images.

Was that better than running the teacher model on the distorted images directly?
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