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Object tracking explained in 3Blue1Brown style. Learn about the tracking loop, kalman filters, why occlusion breaks and one way to fix it. Try it out
129,711 görüntüleme • 1 ay önce •via X (Twitter)
11 Yorum

14 box is huge tf

You are so crack 😍😍😍

Thanks!

Simulated IMU data with heading and gate analyzed. That’s what I would do.

But the core learning from ai is ... Desisit from designing these case specific algorithms.. Just good data and learning for these and 1000 other cases. . delving in single case appears smart but doesn't scale.

i dont think the bitter lesson applies to everything. We still need ligthweight algorithms for a lot of use cases. A big model wont run 30 fps on an edge device, this does

Indeed a good point ... A single fast algorithm has its merit .. the con side is disconnected from a generic web of intelligence ... Breaks at too many edge cases ... Maybe use a very small nn over there ... Many layers are possible..

What type of science or mathematics would this be .

Dude was never seen again!

Just say she's fat

Great explainer - Squash has been my occlusion test; two players in one box, crossing on every shot. Here's how it looks so far
